R Notebook: estimation of impact of arguments on gas costs; for Gas Cost Estimator; for a single given env
In this script we conduct the estimation for the
measure_arguments approach.
PROGRAMS=pg_arguments_full5_c200_opc15x2 SAMPLESIZE=50 NSAMPLES=1`.
Expected a result file erigon_pg_arguments_full5_c200_opc15x2_.csv.
# the programs file is too large to be placed in github
programs = read.csv(paste("../../local/", program_set_codename, ".csv", sep=""))
results = load_data_set(env, program_set_codename, measurement_codename)
# besu may have additional columns with gc stats
results = results[, c("program_id", "sample_id", "run_id", "measure_total_time_ns", "measure_total_timer_time_ns", "env")]
# TODO geth short-circuits zero length programs, resulting in zero timing somehow. Drop these more elegantly, not based on measure_total_time_ns
results = results[which(results$measure_total_time_ns != 0), ]
all_envs = c(env)measurements = sqldf("SELECT opcode, op_count, arg0, arg1, arg2, sample_id, run_id, measure_total_time_ns, env, results.program_id
FROM results
INNER JOIN
programs ON(results.program_id = programs.program_id)
")
measurements$opcode = factor(measurements$opcode, levels=unique(programs$opcode))
head(measurements)## opcode op_count arg0 arg1 arg2 sample_id run_id measure_total_time_ns env
## 1 ADD 0 25 27 NA 0 1 16374 erigon
## 2 ADD 15 25 27 NA 0 1 16331 erigon
## 3 ADD 30 25 27 NA 0 1 16422 erigon
## 4 ADD 0 14 9 NA 0 1 16158 erigon
## 5 ADD 15 14 9 NA 0 1 16281 erigon
## 6 ADD 30 14 9 NA 0 1 16473 erigon
## program_id
## 1 ADD_0
## 2 ADD_1
## 3 ADD_2
## 4 ADD_3
## 5 ADD_4
## 6 ADD_5Remove outliers if needed.
# Extracts all OPCODEs from the `programs` data frame of the given arity (args taken off the stack).
extract_opcodes <- function(arity) {
if (!missing(arity)) {
if (arity == 0) {
programs = programs[which(is.na(programs$arg0) & is.na(programs$arg1) & is.na(programs$arg2)), ]
}
if (arity == 1) {
programs = programs[which(!is.na(programs$arg0) & is.na(programs$arg1) & is.na(programs$arg2)), ]
}
if (arity == 2) {
programs = programs[which(!is.na(programs$arg1) & is.na(programs$arg2)), ]
}
if (arity == 3) {
programs = programs[which(!is.na(programs$arg2)), ]
}
}
unique(programs$opcode)
}if ( (!removed_outliers) && (!removed_outliers_2)) {
boxplot(measure_total_time_ns ~ opcode, data=measurements[which(measurements$env == env), ], las=2, outline=TRUE, log='y', main=paste(env, 'all'))
}if (removed_outliers) {
par(mfrow=c(length(all_envs)*2, 1))
# before
boxplot(measure_total_time_ns ~ opcode, data=measurements[which(measurements$env == env), ], las=2, outline=TRUE, log='y', main=paste(env, 'all'))
measurements = remove_outliers(measurements, 'measure_total_time_ns', FALSE)
# after
boxplot(measure_total_time_ns ~ opcode, data=measurements[which(measurements$env == env), ], las=2, outline=TRUE, log='y', main=paste(env, 'no_outliers'))
}all_opcodes = extract_opcodes()
nullary_opcodes = extract_opcodes(0)
unary_opcodes = extract_opcodes(1)
binary_opcodes = extract_opcodes(2)
ternary_opcodes = extract_opcodes(3)
div_opcodes = c('DIV', 'MOD', 'SDIV', 'SMOD')measurements$expensive = NA
measurements[which(measurements$opcode %in% div_opcodes), ]$expensive =
measurements[which(measurements$opcode %in% div_opcodes), ]$arg0 >
measurements[which(measurements$opcode %in% div_opcodes), ]$arg1
# remember that argX is the byte-size of the argument in these measurements
measurements[which(measurements$opcode == 'ADDMOD'), ]$expensive =
8**measurements[which(measurements$opcode == 'ADDMOD'), ]$arg0 +
8**measurements[which(measurements$opcode == 'ADDMOD'), ]$arg1 >
8**measurements[which(measurements$opcode == 'ADDMOD'), ]$arg2
measurements[which(measurements$opcode == 'MULMOD'), ]$expensive =
measurements[which(measurements$opcode == 'MULMOD'), ]$arg0 +
measurements[which(measurements$opcode == 'MULMOD'), ]$arg1 >
measurements[which(measurements$opcode == 'MULMOD'), ]$arg2if (removed_outliers_2) {
measurements = remove_compare_outliers(measurements, 'measure_total_time_ns', all_envs)
}
Detailed view
This is massive and detailed overview on the impact of arguments.
Because of the number of charts, only op count = 30 is
eligible. Feel free to change it, but that should not be anyhow more
informative. The visualizations do not guarantee that all dependencies
are clearly seen. Especially for binary and ternary opcodes where
impacts of arg0, arg1 and arg2 are mixed. But if a dependency is
graphically noticeable that you should expect also statistical
dependency.
for (env in all_envs) {
for (opcode in unary_opcodes) {
# plot(measure_total_time_ns ~ arg0, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 0), ], pch=0, col='darkgreen')
# title(main = paste(env, opcode, 'arg0', 'opcount 0'))
# plot(measure_total_time_ns ~ arg0, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 15), ], pch=1, col='red')
# title(main = paste(env, opcode, 'arg0', 'opcount 15'))
plot(measure_total_time_ns ~ arg0, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 30), ], pch=5, col='blue')
title(main = paste(env, opcode, 'arg0', 'opcount 30'))
}
for (opcode in binary_opcodes) {
# plot(measure_total_time_ns ~ arg0, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 0), ], pch=0, col='darkgreen')
# title(main = paste(env, opcode, 'arg0', 'opcount 0'))
# plot(measure_total_time_ns ~ arg0, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 15), ], pch=1, col='red')
# title(main = paste(env, opcode, 'arg0', 'opcount 15'))
plot(measure_total_time_ns ~ arg0, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 30), ], pch=5, col='blue')
title(main = paste(env, opcode, 'arg0', 'opcount 30'))
# plot(measure_total_time_ns ~ arg1, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 0), ], pch=0, col='darkgreen')
# title(main = paste(env, opcode, 'arg1', 'opcount 0'))
# plot(measure_total_time_ns ~ arg1, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 15), ], pch=1, col='red')
# title(main = paste(env, opcode, 'arg1', 'opcount 15'))
plot(measure_total_time_ns ~ arg1, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 30), ], pch=5, col='blue')
title(main = paste(env, opcode, 'arg1', 'opcount 30'))
}
for (opcode in ternary_opcodes) {
# plot(measure_total_time_ns ~ arg0, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 0), ], pch=0, col='darkgreen')
# title(main = paste(env, opcode, 'arg0', 'opcount 0'))
# plot(measure_total_time_ns ~ arg0, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 15), ], pch=1, col='red')
# title(main = paste(env, opcode, 'arg0', 'opcount 15'))
plot(measure_total_time_ns ~ arg0, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 30), ], pch=5, col='blue')
title(main = paste(env, opcode, 'arg0', 'opcount 30'))
# plot(measure_total_time_ns ~ arg1, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 0), ], pch=0, col='darkgreen')
# title(main = paste(env, opcode, 'arg1', 'opcount 0'))
# plot(measure_total_time_ns ~ arg1, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 15), ], pch=1, col='red')
# title(main = paste(env, opcode, 'arg1', 'opcount 15'))
plot(measure_total_time_ns ~ arg1, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 30), ], pch=5, col='blue')
title(main = paste(env, opcode, 'arg1', 'opcount 30'))
# plot(measure_total_time_ns ~ arg2, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 0), ], pch=0, col='darkgreen')
# title(main = paste(env, opcode, 'arg2', 'opcount 0'))
# plot(measure_total_time_ns ~ arg2, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 15), ], pch=1, col='red')
# title(main = paste(env, opcode, 'arg2', 'opcount 15'))
plot(measure_total_time_ns ~ arg2, data=measurements[which(measurements$env == env & measurements$opcode == opcode & measurements$op_count == 30), ], pch=5, col='blue')
title(main = paste(env, opcode, 'arg2', 'opcount 30'))
}
}
Models
Notes: 1. Outliers need to be removed if detected 2. The
argX:op_count interactions measure the impact on the OPCODE
3. The argX are just auxiliary variables added to exclude
the effect of cheaper/more expensive PUSHes. We only want to extract the
effect of the argument on the measured OPCODE repeated
op_count times.
# Every `arg` coefficient represents the impact of the argument's byte size growing by 1.
# We treat as impactful the arguments where p-value is effectively zero. The previous approach was:
# Treat as impactful the arguments, where:
# 1. The estimate is significant with confidence 0.001
# 2. The increase of arg's byte size by 1 will increase the cost by more than 1%
# but it turned out to be much less stable in practice.
p_value_thresh = 1e-30
# p_value_thresh = 0.001
impact_ratio = 0.00
# impact_ratio = 0.01
arg_lm <- function(df, opcode, env, formula) {
data = df[which(df$opcode==opcode & df$env==env), ]
lm(formula, data=data)
}
# Adds the results from the estimated `model` to the `results_df` data frame.
# You need to provide the corresponding `opcode`, `env` and `arity`.
# `results_df` is assumed to have the columns as the `first_pass` data frame has (see below)
add_arg_results <- function(model, opcode, env, results_df, arity) {
stopifnot(arity > 0)
all_coefficients = summary(model)$coefficients
arg_coefficients = all_coefficients[!(row.names(all_coefficients) %in% c("op_count", "(Intercept)", "arg0", "arg1", "arg2")),]
pure_op_count_coeff = all_coefficients["op_count", 1]
# will be filled if any is impacting
args_ns = c(NA, NA, NA)
# will be always if arg present
args_ns_raw = c(NA, NA, NA)
args_ns_p = c(NA, NA, NA)
if (arity == 1) {
# there's only one arg coefficient here, silly R forces us to take a special case path...
has_significant = arg_coefficients[4] < p_value_thresh
if (has_significant) {
coefficient_impact = abs(arg_coefficients[1])
has_impacting = has_significant & coefficient_impact > pure_op_count_coeff * impact_ratio
} else {
has_impacting = FALSE
}
if (has_impacting) {
args_ns[1] = arg_coefficients[1]
}
args_ns_raw[1] = arg_coefficients[1]
args_ns_p[1] = arg_coefficients[4]
} else {
significant = arg_coefficients[, 4] < p_value_thresh
has_significant = length(which(significant)) > 0
coefficient_impact = abs(arg_coefficients[, 1])
can_impact = significant & coefficient_impact > pure_op_count_coeff * impact_ratio
has_impacting = length(which(can_impact)) > 0
args_ns[which(can_impact)] = arg_coefficients[which(can_impact), 1]
args_ns_raw[1:arity] = arg_coefficients[1:arity, 1]
args_ns_p[1:arity] = arg_coefficients[1:arity, 4]
}
# NAs for the "expensive" arg columns. See above for the columns layout
results_df[nrow(results_df) + 1, ] = c(opcode, env, has_significant, has_impacting, pure_op_count_coeff, args_ns, NA, args_ns_raw, NA, args_ns_p, NA)
return(results_df)
}
# Adds the results from the estimated `model` to the `results_df` data frame, where the model is
# specifically the one gauged towards the "division" OPCODEs like `DIV`.
# See also `add_arg_results`
add_arg_expensive_results <- function(model, opcode, env, results_df, arity) {
stopifnot(arity > 0)
all_coefficients = summary(model)$coefficients
pure_op_count_coeff = all_coefficients["op_count", 1]
expensive = NA
# there's only one arg coefficient here, silly R forces us to take a special case path...
has_significant = all_coefficients['op_count:expensiveTRUE', 4] < p_value_thresh
if (has_significant) {
coefficient_impact = abs(all_coefficients['op_count:expensiveTRUE', 1])
has_impacting = has_significant & coefficient_impact > pure_op_count_coeff * impact_ratio
} else {
has_impacting = FALSE
}
if (has_impacting) {
expensive = all_coefficients['op_count:expensiveTRUE', 1]
}
expensive_raw = all_coefficients['op_count:expensiveTRUE', 1]
expensive_p = all_coefficients['op_count:expensiveTRUE', 4]
results_df[which(results_df$opcode == opcode & results_df$env == env), 'expensive_ns'] = expensive
results_df[which(results_df$opcode == opcode & results_df$env == env), 'expensive_ns_raw'] = expensive_raw
results_df[which(results_df$opcode == opcode & results_df$env == env), 'expensive_ns_p'] = expensive_p
return(results_df)
}
# Goes through all the families of OPCODEs and fits and displays their respective `measure_arguments`
# models.
# Results are gathered in a common `results_df` data frame.
analyze_for_env <- function(df, results_df, env) {
for (opcode in unary_opcodes) {
model = arg_lm(df, opcode, env, measure_total_time_ns ~ op_count + arg0 + arg0:op_count)
print(c(opcode, env))
print(summary(model))
results_df = add_arg_results(model, opcode, env, results_df, 1)
}
for (opcode in binary_opcodes) {
model = arg_lm(df, opcode, env, measure_total_time_ns ~ op_count + arg0 + arg1 + arg0:op_count + arg1:op_count)
print(c(opcode, env))
print(summary(model))
results_df = add_arg_results(model, opcode, env, results_df, 2)
}
for (opcode in ternary_opcodes) {
model = arg_lm(df, opcode, env, measure_total_time_ns ~ op_count + arg0 + arg1 + arg2 + arg0:op_count + arg1:op_count + arg2:op_count)
print(c(opcode, env))
print(summary(model))
results_df = add_arg_results(model, opcode, env, results_df, 3)
}
for (opcode in div_opcodes) {
model = arg_lm(df, opcode, env, measure_total_time_ns ~ op_count + arg0 + arg1 + expensive:op_count)
print(c(opcode, env))
print(summary(model))
results_df = add_arg_expensive_results(model, opcode, env, results_df, 2)
}
for (opcode in c('ADDMOD', 'MULMOD')) {
model = arg_lm(df, opcode, env, measure_total_time_ns ~ op_count + arg0 + arg1 + arg2 + expensive:op_count)
print(c(opcode, env))
print(summary(model))
results_df = add_arg_expensive_results(model, opcode, env, results_df, 3)
}
return(results_df)
}#model = arg_lm(measurements, 'EXP', env, measure_total_time_ns ~ op_count + arg0 + arg1 + arg0/op_count + arg1/op_count)
model = lm(measure_total_time_ns ~ op_count + arg0 + arg1 + arg0:op_count + arg1:op_count, data=measurements[which(measurements$opcode=='EXP' & measurements$env==env), ])
model##
## Call:
## lm(formula = measure_total_time_ns ~ op_count + arg0 + arg1 +
## arg0:op_count + arg1:op_count, data = measurements[which(measurements$opcode ==
## "EXP" & measurements$env == env), ])
##
## Coefficients:
## (Intercept) op_count arg0 arg1 op_count:arg0
## 16254.3101 -11.7862 -0.8361 1.4283 0.5933
## op_count:arg1
## 84.5865plot(measure_total_time_ns ~ arg1, data=measurements[which(measurements$env == env & measurements$opcode == 'EXP' & measurements$op_count == 0), ], pch=5, col='blue')
title(main = paste(env, 'EXP', 'arg1', 'opcount 0'))
model = lm(measure_total_time_ns ~ arg0 + arg1, data=measurements[which(measurements$opcode=='EXP' & measurements$env==env & measurements$op_count==0), ])
model##
## Call:
## lm(formula = measure_total_time_ns ~ arg0 + arg1, data = measurements[which(measurements$opcode ==
## "EXP" & measurements$env == env & measurements$op_count ==
## 0), ])
##
## Coefficients:
## (Intercept) arg0 arg1
## 16238.7220 -0.2344 1.8163plot(measure_total_time_ns ~ arg1, data=measurements[which(measurements$env == env & measurements$opcode == 'EXP' & measurements$op_count == 15), ], pch=5, col='blue')
title(main = paste(env, 'EXP', 'arg1', 'opcount 15'))
model = lm(measure_total_time_ns ~ arg0 + arg1, data=measurements[which(measurements$opcode=='EXP' & measurements$env==env & measurements$op_count==15), ])
model##
## Call:
## lm(formula = measure_total_time_ns ~ arg0 + arg1, data = measurements[which(measurements$opcode ==
## "EXP" & measurements$env == env & measurements$op_count ==
## 15), ])
##
## Coefficients:
## (Intercept) arg0 arg1
## 16107.211 6.931 1269.472plot(measure_total_time_ns ~ arg1, data=measurements[which(measurements$env == env & measurements$opcode == 'EXP' & measurements$op_count == 30), ], pch=5, col='blue')
title(main = paste(env, 'EXP', 'arg1', 'opcount 30'))
model = lm(measure_total_time_ns ~ arg0 + arg1, data=measurements[which(measurements$opcode=='EXP' & measurements$env==env & measurements$op_count==30), ])
model##
## Call:
## lm(formula = measure_total_time_ns ~ arg0 + arg1, data = measurements[which(measurements$opcode ==
## "EXP" & measurements$env == env & measurements$op_count ==
## 30), ])
##
## Coefficients:
## (Intercept) arg0 arg1
## 15885.88 17.53 2539.40max_m = max(measurements[which(measurements$env == env & measurements$opcode == 'EXP'), 'measure_total_time_ns'])
plot(measure_total_time_ns ~ arg1, data=measurements[which(measurements$env == env & measurements$opcode == 'EXP' & measurements$op_count == 0), ], pch=5, col='red', ylim=c(0,max_m * 1.1))
points(measure_total_time_ns ~ arg1, data=measurements[which(measurements$env == env & measurements$opcode == 'EXP' & measurements$op_count == 15), ], pch=5, col='green', ylim=c(0,max_m * 1.1))
points(measure_total_time_ns ~ arg1, data=measurements[which(measurements$env == env & measurements$opcode == 'EXP' & measurements$op_count == 30), ], pch=5, col='blue', ylim=c(0,max_m * 1.1))
title(main = paste(env, 'EXP', 'arg1'))
This is the so-called “first-pass” at the estimation procedure, where we
estimated all possible argument impact variables for all OPCODEs. We
gather all the results in the first_pass table, inspect
this to see where the arguments turned out to be significantly impacting
the computation cost.
first_pass = data.frame(matrix(ncol = 17, nrow = 0))
colnames(first_pass) <- c('opcode', 'env', 'has_significant', 'has_impacting', 'estimate_marginal_ns',
'arg0_ns', 'arg1_ns', 'arg2_ns', 'expensive_ns',
'arg0_ns_raw', 'arg1_ns_raw', 'arg2_ns_raw', 'expensive_ns_raw',
'arg0_ns_p', 'arg1_ns_p', 'arg2_ns_p', 'expensive_ns_p')
first_pass = analyze_for_env(measurements, first_pass, env)## [1] "ISZERO" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -255.98 -128.04 -48.16 98.06 481.16
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16268.64840 21.17156 768.420 < 0.0000000000000002 ***
## op_count 2.83111 1.09534 2.585 0.00999 **
## arg0 0.93775 1.18655 0.790 0.42967
## op_count:arg0 0.07035 0.06123 1.149 0.25103
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 162.2 on 573 degrees of freedom
## Multiple R-squared: 0.09275, Adjusted R-squared: 0.088
## F-statistic: 19.53 on 3 and 573 DF, p-value: 0.000000000004589
##
## [1] "NOT" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -227.16 -125.84 -60.93 92.29 492.23
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16304.17697 22.85339 713.425 <0.0000000000000002 ***
## op_count 2.83260 1.17264 2.416 0.0160 *
## arg0 -2.01582 1.17051 -1.722 0.0856 .
## op_count:arg0 0.07667 0.06039 1.270 0.2047
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 163 on 575 degrees of freedom
## Multiple R-squared: 0.0931, Adjusted R-squared: 0.08837
## F-statistic: 19.68 on 3 and 575 DF, p-value: 0.000000000003732
##
## [1] "CALLDATALOAD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -139.51 -40.19 -10.20 36.24 175.67
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9254.14029421 8.02958415 1152.506 <0.0000000000000002 ***
## op_count 7.37083323 0.41897559 17.593 <0.0000000000000002 ***
## arg0 0.00124711 0.00079952 1.560 0.119
## op_count:arg0 -0.00006276 0.00004159 -1.509 0.132
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 59.23 on 578 degrees of freedom
## Multiple R-squared: 0.6656, Adjusted R-squared: 0.6638
## F-statistic: 383.4 on 3 and 578 DF, p-value: < 0.00000000000000022
##
## [1] "POP" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -235.24 -111.82 -41.73 78.16 501.61
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14991.67679 19.64893 762.977 < 0.0000000000000002 ***
## op_count 4.01936 1.00515 3.999 0.000072 ***
## arg0 -0.22847 1.02131 -0.224 0.823
## op_count:arg0 0.06801 0.05277 1.289 0.198
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 144.2 on 570 degrees of freedom
## Multiple R-squared: 0.1638, Adjusted R-squared: 0.1594
## F-statistic: 37.21 on 3 and 570 DF, p-value: < 0.00000000000000022
##
## [1] "MLOAD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -140.79 -49.78 -12.69 42.41 211.08
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9280.72588743 9.47404829 979.595 <0.0000000000000002 ***
## op_count 11.67304635 0.48702428 23.968 <0.0000000000000002 ***
## arg0 -0.00094671 0.00091995 -1.029 0.304
## op_count:arg0 0.00006290 0.00004741 1.327 0.185
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 66.93 on 586 degrees of freedom
## Multiple R-squared: 0.8348, Adjusted R-squared: 0.834
## F-statistic: 987.2 on 3 and 586 DF, p-value: < 0.00000000000000022
##
## [1] "JUMPI" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -313.19 -170.40 -8.01 101.26 599.87
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16337.81336 24.70149 661.410 <0.0000000000000002 ***
## op_count 54.51935 1.28557 42.409 <0.0000000000000002 ***
## arg0 0.46118 1.34325 0.343 0.731
## op_count:arg0 -0.04116 0.06962 -0.591 0.555
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 193.8 on 575 degrees of freedom
## Multiple R-squared: 0.921, Adjusted R-squared: 0.9206
## F-statistic: 2235 on 3 and 575 DF, p-value: < 0.00000000000000022
##
## [1] "DUP1" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -249.67 -128.09 -45.21 102.40 449.20
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16248.930461 21.640874 750.844 < 0.0000000000000002 ***
## op_count 6.046401 1.121704 5.390 0.000000103 ***
## arg0 1.216902 1.117920 1.089 0.277
## op_count:arg0 0.002367 0.057966 0.041 0.967
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 156.9 on 578 degrees of freedom
## Multiple R-squared: 0.1885, Adjusted R-squared: 0.1843
## F-statistic: 44.76 on 3 and 578 DF, p-value: < 0.00000000000000022
##
## [1] "DUP2" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -259.78 -124.07 -43.88 95.31 484.46
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16302.70441 20.94868 778.221 < 0.0000000000000002 ***
## op_count 3.91644 1.09142 3.588 0.000362 ***
## arg0 0.25391 1.10799 0.229 0.818826
## op_count:arg0 -0.04145 0.05788 -0.716 0.474270
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 163.5 on 566 degrees of freedom
## Multiple R-squared: 0.05743, Adjusted R-squared: 0.05243
## F-statistic: 11.5 on 3 and 566 DF, p-value: 0.000000252
##
## [1] "DUP3" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -260.18 -136.54 -48.94 101.66 544.63
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16295.56654 23.25092 700.857 < 0.0000000000000002 ***
## op_count 4.21061 1.20007 3.509 0.000485 ***
## arg0 0.03077 1.26016 0.024 0.980528
## op_count:arg0 0.01076 0.06512 0.165 0.868854
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 172.8 on 583 degrees of freedom
## Multiple R-squared: 0.08927, Adjusted R-squared: 0.08459
## F-statistic: 19.05 on 3 and 583 DF, p-value: 0.00000000000851
##
## [1] "DUP4" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -246.56 -128.42 -33.01 92.60 459.40
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16300.84600 21.03442 774.961 < 0.0000000000000002 ***
## op_count 4.26576 1.08343 3.937 0.0000925 ***
## arg0 -1.01591 1.11189 -0.914 0.361
## op_count:arg0 0.03962 0.05732 0.691 0.490
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 158.2 on 576 degrees of freedom
## Multiple R-squared: 0.1282, Adjusted R-squared: 0.1236
## F-statistic: 28.23 on 3 and 576 DF, p-value: < 0.00000000000000022
##
## [1] "DUP5" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -237.04 -131.64 -32.25 101.06 489.04
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16277.52995 20.84523 780.875 < 0.0000000000000002 ***
## op_count 4.92554 1.06600 4.621 0.00000473 ***
## arg0 -0.72863 1.07699 -0.677 0.499
## op_count:arg0 0.05866 0.05519 1.063 0.288
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 157.3 on 571 degrees of freedom
## Multiple R-squared: 0.1779, Adjusted R-squared: 0.1736
## F-statistic: 41.19 on 3 and 571 DF, p-value: < 0.00000000000000022
##
## [1] "DUP6" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -202.99 -118.72 -52.02 93.44 470.52
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16234.428039 21.301404 762.129 < 0.0000000000000002 ***
## op_count 6.853759 1.092400 6.274 0.0000000007 ***
## arg0 0.276766 1.109043 0.250 0.803
## op_count:arg0 -0.007637 0.057067 -0.134 0.894
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 149.6 on 566 degrees of freedom
## Multiple R-squared: 0.2339, Adjusted R-squared: 0.2299
## F-statistic: 57.62 on 3 and 566 DF, p-value: < 0.00000000000000022
##
## [1] "DUP7" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -251.63 -135.09 -68.61 99.61 539.82
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16307.65432 23.41856 696.356 < 0.0000000000000002 ***
## op_count 4.70747 1.21515 3.874 0.000119 ***
## arg0 -1.50644 1.25702 -1.198 0.231239
## op_count:arg0 0.04800 0.06501 0.738 0.460550
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 171.7 on 582 degrees of freedom
## Multiple R-squared: 0.1358, Adjusted R-squared: 0.1314
## F-statistic: 30.5 on 3 and 582 DF, p-value: < 0.00000000000000022
##
## [1] "DUP8" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -287.2 -148.7 -23.4 113.3 521.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16332.46612 22.29426 732.586 <0.0000000000000002 ***
## op_count 13.99581 1.14594 12.213 <0.0000000000000002 ***
## arg0 -0.92205 1.29068 -0.714 0.475
## op_count:arg0 0.06897 0.06615 1.043 0.298
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 172.8 on 579 degrees of freedom
## Multiple R-squared: 0.5338, Adjusted R-squared: 0.5313
## F-statistic: 221 on 3 and 579 DF, p-value: < 0.00000000000000022
##
## [1] "DUP9" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -239.36 -121.66 -58.41 90.52 530.33
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16254.63148 21.88792 742.630 < 0.0000000000000002 ***
## op_count 6.43870 1.13311 5.682 0.0000000212 ***
## arg0 0.72418 1.19124 0.608 0.543
## op_count:arg0 -0.07102 0.06166 -1.152 0.250
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 161.4 on 569 degrees of freedom
## Multiple R-squared: 0.1435, Adjusted R-squared: 0.1389
## F-statistic: 31.77 on 3 and 569 DF, p-value: < 0.00000000000000022
##
## [1] "DUP10" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -214.62 -123.03 -65.82 84.16 540.67
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16269.68538 22.78002 714.208 < 0.0000000000000002 ***
## op_count 5.38234 1.17984 4.562 0.00000621 ***
## arg0 -0.43332 1.14185 -0.379 0.704
## op_count:arg0 0.02303 0.05870 0.392 0.695
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 164.2 on 568 degrees of freedom
## Multiple R-squared: 0.1577, Adjusted R-squared: 0.1533
## F-statistic: 35.46 on 3 and 568 DF, p-value: < 0.00000000000000022
##
## [1] "DUP11" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -236.35 -132.52 -57.62 102.69 513.65
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16515.99369 23.12853 714.096 < 0.0000000000000002 ***
## op_count 7.12853 1.19567 5.962 0.00000000434 ***
## arg0 1.13604 1.21149 0.938 0.349
## op_count:arg0 -0.05810 0.06286 -0.924 0.356
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 168.2 on 578 degrees of freedom
## Multiple R-squared: 0.1697, Adjusted R-squared: 0.1654
## F-statistic: 39.38 on 3 and 578 DF, p-value: < 0.00000000000000022
##
## [1] "DUP12" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -247.1 -136.7 -39.2 109.2 544.2
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16240.09435 21.82911 743.965 < 0.0000000000000002 ***
## op_count 6.77723 1.12564 6.021 0.00000000309 ***
## arg0 2.47320 1.15645 2.139 0.0329 *
## op_count:arg0 -0.05974 0.05964 -1.002 0.3169
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 167.6 on 576 degrees of freedom
## Multiple R-squared: 0.1598, Adjusted R-squared: 0.1555
## F-statistic: 36.53 on 3 and 576 DF, p-value: < 0.00000000000000022
##
## [1] "DUP13" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -252.55 -128.31 -53.09 96.08 483.14
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16300.828218 22.933165 710.797 < 0.0000000000000002 ***
## op_count 4.533328 1.183132 3.832 0.000141 ***
## arg0 -1.069487 1.179125 -0.907 0.364776
## op_count:arg0 -0.003808 0.060554 -0.063 0.949879
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 163.2 on 577 degrees of freedom
## Multiple R-squared: 0.1046, Adjusted R-squared: 0.09995
## F-statistic: 22.47 on 3 and 577 DF, p-value: 0.00000000000009013
##
## [1] "DUP14" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -207.62 -112.96 -44.55 84.63 401.86
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16250.46192 19.21578 845.683 < 0.0000000000000002 ***
## op_count 6.26380 0.99125 6.319 0.000000000538 ***
## arg0 0.86817 1.04006 0.835 0.4042
## op_count:arg0 -0.11515 0.05354 -2.151 0.0319 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 141.3 on 559 degrees of freedom
## Multiple R-squared: 0.1373, Adjusted R-squared: 0.1327
## F-statistic: 29.65 on 3 and 559 DF, p-value: < 0.00000000000000022
##
## [1] "DUP15" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -240.62 -131.44 -48.37 98.84 498.59
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16311.93036 24.20527 673.900 < 0.0000000000000002 ***
## op_count 3.31997 1.26402 2.627 0.00885 **
## arg0 -1.30105 1.25205 -1.039 0.29918
## op_count:arg0 0.06674 0.06520 1.024 0.30643
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 165.4 on 580 degrees of freedom
## Multiple R-squared: 0.1012, Adjusted R-squared: 0.0966
## F-statistic: 21.78 on 3 and 580 DF, p-value: 0.0000000000002235
##
## [1] "DUP16" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -276.59 -152.73 -34.02 108.96 624.98
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16875.00112 24.91216 677.380 <0.0000000000000002 ***
## op_count 15.45153 1.28175 12.055 <0.0000000000000002 ***
## arg0 -0.53064 1.29674 -0.409 0.683
## op_count:arg0 -0.04141 0.06674 -0.620 0.535
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 182.7 on 576 degrees of freedom
## Multiple R-squared: 0.499, Adjusted R-squared: 0.4964
## F-statistic: 191.3 on 3 and 576 DF, p-value: < 0.00000000000000022
##
## [1] "ADD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -246.10 -131.49 -46.43 94.83 526.44
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16234.26510 30.71563 528.534 < 0.0000000000000002 ***
## op_count 7.28432 1.56483 4.655 0.00000404 ***
## arg0 2.30792 1.19787 1.927 0.0545 .
## arg1 -0.47372 1.17715 -0.402 0.6875
## op_count:arg0 -0.07614 0.06145 -1.239 0.2158
## op_count:arg1 0.03762 0.06000 0.627 0.5309
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 162 on 567 degrees of freedom
## Multiple R-squared: 0.2106, Adjusted R-squared: 0.2036
## F-statistic: 30.25 on 5 and 567 DF, p-value: < 0.00000000000000022
##
## [1] "MUL" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -261.02 -136.09 -60.53 102.29 569.14
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16326.57577 31.51275 518.094 < 0.0000000000000002 ***
## op_count 7.21799 1.63502 4.415 0.0000121 ***
## arg0 -1.86762 1.23975 -1.506 0.133
## arg1 -0.22798 1.25906 -0.181 0.856
## op_count:arg0 0.04688 0.06427 0.729 0.466
## op_count:arg1 -0.01226 0.06467 -0.190 0.850
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 170.6 on 568 degrees of freedom
## Multiple R-squared: 0.2467, Adjusted R-squared: 0.2401
## F-statistic: 37.2 on 5 and 568 DF, p-value: < 0.00000000000000022
##
## [1] "SUB" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -247.15 -154.00 -53.39 103.13 588.21
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16316.91378 33.72328 483.847 < 0.0000000000000002 ***
## op_count 5.46127 1.75465 3.112 0.00195 **
## arg0 -0.10630 1.34560 -0.079 0.93706
## arg1 -0.33334 1.32323 -0.252 0.80120
## op_count:arg0 0.01889 0.06957 0.272 0.78603
## op_count:arg1 -0.03182 0.06890 -0.462 0.64441
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 181.8 on 576 degrees of freedom
## Multiple R-squared: 0.1128, Adjusted R-squared: 0.1051
## F-statistic: 14.65 on 5 and 576 DF, p-value: 0.0000000000001557
##
## [1] "DIV" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -604.46 -153.18 -32.82 129.49 976.26
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16245.78343 43.14031 376.580 < 0.0000000000000002 ***
## op_count 9.96677 2.21146 4.507 0.0000079614151016 ***
## arg0 0.97507 1.71600 0.568 0.57010
## arg1 0.74944 1.68634 0.444 0.65690
## op_count:arg0 0.69820 0.08828 7.909 0.0000000000000132 ***
## op_count:arg1 -0.26964 0.08647 -3.118 0.00191 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 241.1 on 580 degrees of freedom
## Multiple R-squared: 0.5225, Adjusted R-squared: 0.5184
## F-statistic: 126.9 on 5 and 580 DF, p-value: < 0.00000000000000022
##
## [1] "SDIV" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -663.1 -149.4 -34.2 140.6 965.1
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16269.30373 40.82235 398.539 < 0.0000000000000002 ***
## op_count 12.12861 2.07695 5.840 0.00000000869 ***
## arg0 -0.75051 1.63838 -0.458 0.647
## arg1 1.08644 1.63088 0.666 0.506
## op_count:arg0 0.76653 0.08407 9.118 < 0.0000000000000002 ***
## op_count:arg1 -0.33616 0.08370 -4.016 0.00006692759 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 228.9 on 584 degrees of freedom
## Multiple R-squared: 0.5929, Adjusted R-squared: 0.5894
## F-statistic: 170.1 on 5 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "MOD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -562.79 -155.97 -20.11 130.20 1213.93
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16295.37139 42.09240 387.133 < 0.0000000000000002 ***
## op_count 10.49327 2.16851 4.839 0.00000167068886893 ***
## arg0 0.79710 1.65088 0.483 0.6294
## arg1 -1.59845 1.67346 -0.955 0.3399
## op_count:arg0 0.68146 0.08501 8.016 0.00000000000000593 ***
## op_count:arg1 -0.18626 0.08601 -2.166 0.0307 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 235.2 on 587 degrees of freedom
## Multiple R-squared: 0.5776, Adjusted R-squared: 0.574
## F-statistic: 160.6 on 5 and 587 DF, p-value: < 0.00000000000000022
##
## [1] "SMOD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -576.46 -163.72 -29.33 121.49 1021.46
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16288.55948 41.56712 391.862 < 0.0000000000000002 ***
## op_count 10.88216 2.12205 5.128 0.00000039884832997 ***
## arg0 1.32968 1.58123 0.841 0.4007
## arg1 -0.81243 1.72636 -0.471 0.6381
## op_count:arg0 0.68060 0.08135 8.366 0.00000000000000044 ***
## op_count:arg1 -0.16097 0.08844 -1.820 0.0693 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 228.3 on 583 degrees of freedom
## Multiple R-squared: 0.5908, Adjusted R-squared: 0.5872
## F-statistic: 168.3 on 5 and 583 DF, p-value: < 0.00000000000000022
##
## [1] "EXP" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4017.7 -238.3 -22.3 321.9 4387.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16254.3101 128.4929 126.500 <0.0000000000000002 ***
## op_count -11.7862 6.5889 -1.789 0.0742 .
## arg0 -0.8361 5.5134 -0.152 0.8795
## arg1 1.4283 5.2634 0.271 0.7862
## op_count:arg0 0.5933 0.2818 2.105 0.0357 *
## op_count:arg1 84.5865 0.2702 313.044 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 783.4 on 588 degrees of freedom
## Multiple R-squared: 0.9989, Adjusted R-squared: 0.9989
## F-statistic: 1.042e+05 on 5 and 588 DF, p-value: < 0.00000000000000022
##
## [1] "SIGNEXTEND" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -248.61 -120.95 -52.73 98.64 490.89
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16284.48068 26.88717 605.660 < 0.0000000000000002 ***
## op_count 8.29110 1.38968 5.966 0.00000000425 ***
## arg0 -0.59915 1.08024 -0.555 0.579
## arg1 -0.27341 1.10954 -0.246 0.805
## op_count:arg0 -0.03452 0.05568 -0.620 0.535
## op_count:arg1 -0.05238 0.05749 -0.911 0.363
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 154.8 on 574 degrees of freedom
## Multiple R-squared: 0.2365, Adjusted R-squared: 0.2299
## F-statistic: 35.56 on 5 and 574 DF, p-value: < 0.00000000000000022
##
## [1] "LT" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -226.14 -120.82 -56.97 94.91 459.79
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16286.281847 28.925592 563.041 < 0.0000000000000002 ***
## op_count 7.517933 1.485606 5.061 0.000000567 ***
## arg0 -0.544934 1.140749 -0.478 0.633
## arg1 -1.369839 1.171247 -1.170 0.243
## op_count:arg0 -0.049882 0.058570 -0.852 0.395
## op_count:arg1 0.001335 0.060119 0.022 0.982
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 153.8 on 564 degrees of freedom
## Multiple R-squared: 0.2327, Adjusted R-squared: 0.2259
## F-statistic: 34.2 on 5 and 564 DF, p-value: < 0.00000000000000022
##
## [1] "GT" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -236.40 -126.75 -49.46 91.15 535.94
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16312.46786 28.73554 567.676 < 0.0000000000000002 ***
## op_count 4.12995 1.51176 2.732 0.00649 **
## arg0 -1.10961 1.20874 -0.918 0.35901
## arg1 -0.72346 1.16739 -0.620 0.53569
## op_count:arg0 0.06286 0.06317 0.995 0.32009
## op_count:arg1 0.02129 0.06051 0.352 0.72504
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 161.1 on 569 degrees of freedom
## Multiple R-squared: 0.1528, Adjusted R-squared: 0.1454
## F-statistic: 20.53 on 5 and 569 DF, p-value: < 0.00000000000000022
##
## [1] "SLT" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -254.83 -136.37 -61.15 100.61 551.67
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16281.2565037 32.9744540 493.754 < 0.0000000000000002 ***
## op_count 6.5931712 1.7024688 3.873 0.00012 ***
## arg0 -0.5060530 1.2276859 -0.412 0.68035
## arg1 0.1621553 1.1899771 0.136 0.89166
## op_count:arg0 0.1125977 0.0632958 1.779 0.07578 .
## op_count:arg1 -0.0005925 0.0612829 -0.010 0.99229
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 169.5 on 572 degrees of freedom
## Multiple R-squared: 0.2843, Adjusted R-squared: 0.278
## F-statistic: 45.43 on 5 and 572 DF, p-value: < 0.00000000000000022
##
## [1] "SGT" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -264.51 -137.29 -44.83 104.40 529.11
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16272.00850 31.04030 524.222 < 0.0000000000000002 ***
## op_count 9.93190 1.60283 6.196 0.0000000011 ***
## arg0 0.79828 1.33644 0.597 0.551
## arg1 -0.39922 1.19881 -0.333 0.739
## op_count:arg0 -0.05439 0.06914 -0.787 0.432
## op_count:arg1 -0.03643 0.06228 -0.585 0.559
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 172.9 on 580 degrees of freedom
## Multiple R-squared: 0.2694, Adjusted R-squared: 0.2631
## F-statistic: 42.77 on 5 and 580 DF, p-value: < 0.00000000000000022
##
## [1] "EQ" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -243.76 -124.05 -61.03 98.36 508.37
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16273.38567 29.68575 548.188 < 0.0000000000000002 ***
## op_count 6.45367 1.51012 4.274 0.0000226 ***
## arg0 0.43176 1.17626 0.367 0.714
## arg1 -1.33431 1.24044 -1.076 0.283
## op_count:arg0 -0.09358 0.05998 -1.560 0.119
## op_count:arg1 0.06704 0.06334 1.058 0.290
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 164.8 on 566 degrees of freedom
## Multiple R-squared: 0.1816, Adjusted R-squared: 0.1744
## F-statistic: 25.12 on 5 and 566 DF, p-value: < 0.00000000000000022
##
## [1] "AND" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -257.13 -133.49 -58.29 90.82 544.90
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16298.53276 29.05652 560.925 < 0.0000000000000002 ***
## op_count 5.83992 1.51623 3.852 0.000131 ***
## arg0 -1.36128 1.16572 -1.168 0.243390
## arg1 0.55498 1.25071 0.444 0.657404
## op_count:arg0 0.02304 0.06042 0.381 0.703146
## op_count:arg1 -0.05990 0.06491 -0.923 0.356479
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 168.8 on 571 degrees of freedom
## Multiple R-squared: 0.1299, Adjusted R-squared: 0.1223
## F-statistic: 17.05 on 5 and 571 DF, p-value: 0.0000000000000009802
##
## [1] "OR" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -271.04 -131.08 -45.89 97.64 506.92
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16214.23292 29.28762 553.621 < 0.0000000000000002 ***
## op_count 7.85416 1.51681 5.178 0.000000311 ***
## arg0 0.60287 1.20567 0.500 0.6172
## arg1 2.73442 1.19004 2.298 0.0219 *
## op_count:arg0 -0.01742 0.06156 -0.283 0.7773
## op_count:arg1 -0.07534 0.06164 -1.222 0.2221
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 163.9 on 574 degrees of freedom
## Multiple R-squared: 0.1902, Adjusted R-squared: 0.1832
## F-statistic: 26.97 on 5 and 574 DF, p-value: < 0.00000000000000022
##
## [1] "XOR" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -290.01 -127.95 -40.29 102.20 578.07
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16312.27430 28.71292 568.116 <0.0000000000000002 ***
## op_count 3.82609 1.48501 2.576 0.0102 *
## arg0 -1.47177 1.14504 -1.285 0.1992
## arg1 1.26653 1.15592 1.096 0.2737
## op_count:arg0 0.02093 0.05974 0.350 0.7263
## op_count:arg1 -0.03056 0.06001 -0.509 0.6108
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 165.6 on 570 degrees of freedom
## Multiple R-squared: 0.07479, Adjusted R-squared: 0.06667
## F-statistic: 9.215 on 5 and 570 DF, p-value: 0.00000001901
##
## [1] "BYTE" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -237.58 -131.52 -56.08 87.95 516.96
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16296.69807 32.50637 501.339 < 0.0000000000000002 ***
## op_count 7.21115 1.67708 4.300 0.0000201 ***
## arg0 -0.98462 1.29508 -0.760 0.447
## arg1 -1.05029 1.26997 -0.827 0.409
## op_count:arg0 -0.04491 0.06597 -0.681 0.496
## op_count:arg1 0.01670 0.06489 0.257 0.797
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 169.7 on 573 degrees of freedom
## Multiple R-squared: 0.1968, Adjusted R-squared: 0.1898
## F-statistic: 28.08 on 5 and 573 DF, p-value: < 0.00000000000000022
##
## [1] "SHL" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -249.54 -130.86 -49.66 95.39 514.54
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16259.56680 28.52900 569.931 < 0.0000000000000002 ***
## op_count 5.53073 1.49196 3.707 0.00023 ***
## arg0 1.05543 1.13747 0.928 0.35387
## arg1 0.40409 1.18019 0.342 0.73218
## op_count:arg0 -0.03464 0.05930 -0.584 0.55938
## op_count:arg1 -0.03637 0.06103 -0.596 0.55144
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 163.3 on 568 degrees of freedom
## Multiple R-squared: 0.1005, Adjusted R-squared: 0.09256
## F-statistic: 12.69 on 5 and 568 DF, p-value: 0.0000000000105
##
## [1] "SHR" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -248.22 -130.65 -59.03 98.86 521.81
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16322.12548 27.19609 600.164 <0.0000000000000002 ***
## op_count 2.71938 1.40307 1.938 0.0531 .
## arg0 -2.19686 1.18921 -1.847 0.0652 .
## arg1 -1.25245 1.16991 -1.071 0.2848
## op_count:arg0 0.06062 0.06165 0.983 0.3259
## op_count:arg1 0.13654 0.06032 2.264 0.0240 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 165.6 on 573 degrees of freedom
## Multiple R-squared: 0.1719, Adjusted R-squared: 0.1647
## F-statistic: 23.8 on 5 and 573 DF, p-value: < 0.00000000000000022
##
## [1] "SAR" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -256.34 -135.05 -57.52 102.53 552.17
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16267.755211 33.449309 486.341 < 0.0000000000000002 ***
## op_count 6.585323 1.725722 3.816 0.00015 ***
## arg0 0.471124 1.268001 0.372 0.71036
## arg1 1.374196 1.260774 1.090 0.27618
## op_count:arg0 -0.073407 0.065629 -1.119 0.26381
## op_count:arg1 0.008271 0.065178 0.127 0.89907
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 173.1 on 579 degrees of freedom
## Multiple R-squared: 0.1436, Adjusted R-squared: 0.1362
## F-statistic: 19.41 on 5 and 579 DF, p-value: < 0.00000000000000022
##
## [1] "MSTORE" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -182.321 -47.798 -6.315 40.557 222.608
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8091.54363179 12.76889238 633.692 <0.0000000000000002 ***
## op_count 58.93984323 0.65874775 89.473 <0.0000000000000002 ***
## arg0 0.00105227 0.00099425 1.058 0.2903
## arg1 0.00093194 0.00096904 0.962 0.3366
## op_count:arg0 -0.00009836 0.00005119 -1.921 0.0552 .
## op_count:arg1 -0.00005755 0.00004991 -1.153 0.2493
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 72.08 on 582 degrees of freedom
## Multiple R-squared: 0.9899, Adjusted R-squared: 0.9898
## F-statistic: 1.141e+04 on 5 and 582 DF, p-value: < 0.00000000000000022
##
## [1] "MSTORE8" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -139.067 -36.603 -1.479 34.042 157.075
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8083.34653795 8.91279651 906.937 <0.0000000000000002 ***
## op_count 12.88297744 0.45656440 28.217 <0.0000000000000002 ***
## arg0 0.00076728 0.00074125 1.035 0.301
## arg1 0.00052198 0.00074446 0.701 0.483
## op_count:arg0 -0.00005841 0.00003809 -1.533 0.126
## op_count:arg1 0.00001550 0.00003828 0.405 0.686
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 51.9 on 582 degrees of freedom
## Multiple R-squared: 0.8981, Adjusted R-squared: 0.8972
## F-statistic: 1025 on 5 and 582 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP1" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -209.05 -107.90 -45.57 83.02 444.18
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14973.87316 26.14205 572.789 < 0.0000000000000002 ***
## op_count 7.26297 1.34661 5.394 0.000000102 ***
## arg0 -0.11010 1.03690 -0.106 0.915
## arg1 1.28638 1.01783 1.264 0.207
## op_count:arg0 -0.04627 0.05387 -0.859 0.391
## op_count:arg1 -0.04433 0.05247 -0.845 0.399
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 143.8 on 564 degrees of freedom
## Multiple R-squared: 0.2022, Adjusted R-squared: 0.1951
## F-statistic: 28.59 on 5 and 564 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP2" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -200.7 -107.5 -45.6 88.9 409.4
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14996.501523 25.037150 598.970 < 0.0000000000000002 ***
## op_count 5.416396 1.319755 4.104 0.0000466 ***
## arg0 -0.554100 1.024650 -0.541 0.589
## arg1 0.551645 0.958993 0.575 0.565
## op_count:arg0 0.023603 0.053392 0.442 0.659
## op_count:arg1 -0.007307 0.050167 -0.146 0.884
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 136.7 on 566 degrees of freedom
## Multiple R-squared: 0.2068, Adjusted R-squared: 0.1998
## F-statistic: 29.52 on 5 and 566 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP3" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -220.78 -118.00 -39.27 83.30 452.50
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14997.24697 25.83260 580.555 < 0.0000000000000002 ***
## op_count 4.93042 1.34194 3.674 0.000261 ***
## arg0 0.63017 1.03476 0.609 0.542769
## arg1 0.05891 1.00857 0.058 0.953443
## op_count:arg0 -0.01616 0.05359 -0.302 0.763076
## op_count:arg1 0.04589 0.05185 0.885 0.376502
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 146.1 on 572 degrees of freedom
## Multiple R-squared: 0.1753, Adjusted R-squared: 0.1681
## F-statistic: 24.32 on 5 and 572 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP4" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -195.16 -101.71 -42.06 77.47 428.69
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14975.95964 24.49301 611.438 < 0.0000000000000002 ***
## op_count 6.52564 1.26486 5.159 0.000000345 ***
## arg0 0.62689 1.00237 0.625 0.532
## arg1 -1.01911 0.98083 -1.039 0.299
## op_count:arg0 -0.03550 0.05164 -0.687 0.492
## op_count:arg1 0.05828 0.05007 1.164 0.245
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 134.1 on 559 degrees of freedom
## Multiple R-squared: 0.2857, Adjusted R-squared: 0.2793
## F-statistic: 44.71 on 5 and 559 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP5" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -207.88 -120.38 -54.47 96.88 473.83
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15003.68037 28.13941 533.191 < 0.0000000000000002 ***
## op_count 4.41532 1.45113 3.043 0.00245 **
## arg0 -0.46092 1.05575 -0.437 0.66258
## arg1 0.32971 1.12625 0.293 0.76982
## op_count:arg0 0.02700 0.05422 0.498 0.61868
## op_count:arg1 0.05347 0.05826 0.918 0.35909
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 147.3 on 576 degrees of freedom
## Multiple R-squared: 0.1895, Adjusted R-squared: 0.1825
## F-statistic: 26.93 on 5 and 576 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP6" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -223.31 -121.05 -55.14 89.18 473.23
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15277.52952 29.56271 516.784 < 0.0000000000000002 ***
## op_count 5.06008 1.52603 3.316 0.000971 ***
## arg0 0.52634 1.12948 0.466 0.641390
## arg1 -0.84566 1.10459 -0.766 0.444235
## op_count:arg0 -0.03800 0.05831 -0.652 0.514919
## op_count:arg1 0.12342 0.05732 2.153 0.031731 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 157 on 575 degrees of freedom
## Multiple R-squared: 0.2147, Adjusted R-squared: 0.2079
## F-statistic: 31.45 on 5 and 575 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP7" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -201.71 -108.05 -51.64 81.79 415.24
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15281.81046 25.36212 602.545 < 0.0000000000000002 ***
## op_count 4.84499 1.30034 3.726 0.000214 ***
## arg0 -1.58267 1.02218 -1.548 0.122097
## arg1 -0.48993 1.04714 -0.468 0.640056
## op_count:arg0 0.07978 0.05279 1.511 0.131284
## op_count:arg1 0.04538 0.05430 0.836 0.403713
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 136.3 on 571 degrees of freedom
## Multiple R-squared: 0.2866, Adjusted R-squared: 0.2804
## F-statistic: 45.88 on 5 and 571 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP8" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -218.00 -124.14 -50.92 95.11 479.23
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15019.06919 27.48947 546.357 < 0.0000000000000002 ***
## op_count 5.06091 1.41368 3.580 0.000373 ***
## arg0 1.32776 1.12539 1.180 0.238559
## arg1 -1.51618 1.16072 -1.306 0.191997
## op_count:arg0 -0.05067 0.05812 -0.872 0.383597
## op_count:arg1 0.07296 0.05955 1.225 0.221029
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 158.7 on 574 degrees of freedom
## Multiple R-squared: 0.1536, Adjusted R-squared: 0.1462
## F-statistic: 20.83 on 5 and 574 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP9" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -202.97 -109.77 -44.75 80.63 428.24
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14938.93539 26.71146 559.271 < 0.0000000000000002 ***
## op_count 7.70491 1.37509 5.603 0.0000000327 ***
## arg0 2.46521 1.03236 2.388 0.0173 *
## arg1 0.22175 0.98518 0.225 0.8220
## op_count:arg0 -0.10054 0.05336 -1.884 0.0600 .
## op_count:arg1 0.01036 0.05092 0.203 0.8388
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 137 on 572 degrees of freedom
## Multiple R-squared: 0.2439, Adjusted R-squared: 0.2373
## F-statistic: 36.91 on 5 and 572 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP10" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -217.41 -116.95 -53.92 88.21 496.18
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15529.62330 28.25080 549.706 < 0.0000000000000002 ***
## op_count 6.29292 1.47171 4.276 0.0000224 ***
## arg0 1.04962 1.02601 1.023 0.307
## arg1 0.89996 1.12859 0.797 0.426
## op_count:arg0 -0.02234 0.05335 -0.419 0.676
## op_count:arg1 -0.05881 0.05868 -1.002 0.317
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 147.7 on 563 degrees of freedom
## Multiple R-squared: 0.1477, Adjusted R-squared: 0.1401
## F-statistic: 19.51 on 5 and 563 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP11" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -229.07 -121.11 -60.39 90.18 541.71
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14966.44743 27.94491 535.570 < 0.0000000000000002 ***
## op_count 6.92235 1.43663 4.818 0.00000186 ***
## arg0 1.79868 1.14949 1.565 0.118
## arg1 1.44712 1.14704 1.262 0.208
## op_count:arg0 -0.05085 0.05927 -0.858 0.391
## op_count:arg1 -0.07148 0.05967 -1.198 0.231
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 156.6 on 568 degrees of freedom
## Multiple R-squared: 0.1367, Adjusted R-squared: 0.1291
## F-statistic: 17.98 on 5 and 568 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP12" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -219.05 -107.61 -49.05 85.21 441.03
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15251.70118 23.93293 637.268 < 0.0000000000000002 ***
## op_count 5.71129 1.22495 4.662 0.00000391 ***
## arg0 0.24035 1.01544 0.237 0.813
## arg1 -0.62897 1.03150 -0.610 0.542
## op_count:arg0 0.05692 0.05151 1.105 0.270
## op_count:arg1 0.04344 0.05270 0.824 0.410
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 141.5 on 557 degrees of freedom
## Multiple R-squared: 0.2993, Adjusted R-squared: 0.293
## F-statistic: 47.59 on 5 and 557 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP13" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -217.93 -117.58 -40.26 91.58 422.24
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15272.90129 24.67636 618.929 < 0.0000000000000002 ***
## op_count 5.60987 1.27747 4.391 0.0000134 ***
## arg0 -0.20470 1.03421 -0.198 0.843
## arg1 1.61256 1.02470 1.574 0.116
## op_count:arg0 0.01948 0.05368 0.363 0.717
## op_count:arg1 -0.04283 0.05294 -0.809 0.419
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 145.7 on 572 degrees of freedom
## Multiple R-squared: 0.1698, Adjusted R-squared: 0.1626
## F-statistic: 23.41 on 5 and 572 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP14" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -241.28 -111.90 -35.52 79.31 485.79
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15004.86710 24.59991 609.956 < 0.0000000000000002 ***
## op_count 5.52005 1.28118 4.309 0.0000194 ***
## arg0 1.14665 1.06623 1.075 0.283
## arg1 -0.04041 1.01572 -0.040 0.968
## op_count:arg0 -0.07896 0.05585 -1.414 0.158
## op_count:arg1 0.01276 0.05290 0.241 0.810
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 142.7 on 570 degrees of freedom
## Multiple R-squared: 0.1342, Adjusted R-squared: 0.1266
## F-statistic: 17.67 on 5 and 570 DF, p-value: 0.0000000000000002688
##
## [1] "SWAP15" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -229.95 -95.57 -43.78 77.86 461.93
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15782.53262 24.58860 641.864 < 0.0000000000000002 ***
## op_count 7.15043 1.27476 5.609 0.0000000319 ***
## arg0 0.05366 0.93461 0.057 0.954
## arg1 -1.49402 0.93974 -1.590 0.112
## op_count:arg0 -0.03870 0.04879 -0.793 0.428
## op_count:arg1 0.06245 0.04869 1.283 0.200
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 130.9 on 564 degrees of freedom
## Multiple R-squared: 0.3418, Adjusted R-squared: 0.3359
## F-statistic: 58.57 on 5 and 564 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP16" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -216.12 -102.26 -55.91 91.00 428.31
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15503.86954 25.57975 606.099 < 0.0000000000000002 ***
## op_count 6.48629 1.30677 4.964 0.000000917 ***
## arg0 -0.15086 0.97948 -0.154 0.878
## arg1 1.09281 1.04639 1.044 0.297
## op_count:arg0 0.06705 0.04970 1.349 0.178
## op_count:arg1 -0.03467 0.05347 -0.649 0.517
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 139.1 on 566 degrees of freedom
## Multiple R-squared: 0.2814, Adjusted R-squared: 0.2751
## F-statistic: 44.33 on 5 and 566 DF, p-value: < 0.00000000000000022
##
## [1] "ADDMOD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -694.51 -162.00 -13.49 144.03 855.14
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16342.39218 57.19645 285.724 < 0.0000000000000002 ***
## op_count 10.79980 2.92991 3.686 0.000249 ***
## arg0 -0.75362 1.71083 -0.441 0.659741
## arg1 -1.57487 1.77799 -0.886 0.376118
## arg2 0.21297 1.87686 0.113 0.909694
## op_count:arg0 0.50048 0.08783 5.698 0.0000000193585 ***
## op_count:arg1 0.62504 0.09096 6.872 0.0000000000166 ***
## op_count:arg2 -0.23615 0.09620 -2.455 0.014396 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 248.2 on 575 degrees of freedom
## Multiple R-squared: 0.6754, Adjusted R-squared: 0.6714
## F-statistic: 170.9 on 7 and 575 DF, p-value: < 0.00000000000000022
##
## [1] "MULMOD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -749.98 -151.32 -17.47 132.38 989.54
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16283.351022 49.355738 329.918 < 0.0000000000000002 ***
## op_count 16.306501 2.549354 6.396 0.000000000326 ***
## arg0 -0.225178 1.614504 -0.139 0.889
## arg1 0.999143 1.675812 0.596 0.551
## arg2 -0.732822 1.659556 -0.442 0.659
## op_count:arg0 0.945613 0.083674 11.301 < 0.0000000000000002 ***
## op_count:arg1 0.843751 0.086665 9.736 < 0.0000000000000002 ***
## op_count:arg2 -0.007326 0.085406 -0.086 0.932
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 240.3 on 584 degrees of freedom
## Multiple R-squared: 0.8634, Adjusted R-squared: 0.8618
## F-statistic: 527.4 on 7 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "CALLDATACOPY" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1087.20 -64.40 -5.64 67.64 522.59
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8111.43723890 27.74111627 292.398 <0.0000000000000002 ***
## op_count 26.60034327 1.41871423 18.750 <0.0000000000000002 ***
## arg0 0.00046362 0.00191528 0.242 0.809
## arg1 -0.00082720 0.00199754 -0.414 0.679
## arg2 0.00238572 0.00182548 1.307 0.192
## op_count:arg0 0.00001571 0.00009837 0.160 0.873
## op_count:arg1 -0.00007119 0.00010230 -0.696 0.487
## op_count:arg2 0.00653350 0.00009358 69.814 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 136.6 on 585 degrees of freedom
## Multiple R-squared: 0.9864, Adjusted R-squared: 0.9863
## F-statistic: 6076 on 7 and 585 DF, p-value: < 0.00000000000000022
##
## [1] "CODECOPY" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5364.6 -460.5 20.6 364.4 8467.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10854.7074220 354.8521983 30.589 < 0.0000000000000002 ***
## op_count 54.7746244 18.1044615 3.025 0.00259 **
## arg0 -0.0017448 0.0229158 -0.076 0.93933
## arg1 0.0020223 0.0226147 0.089 0.92878
## arg2 0.0027127 0.0233120 0.116 0.90740
## op_count:arg0 0.0004654 0.0011694 0.398 0.69077
## op_count:arg1 -0.0023437 0.0011548 -2.029 0.04287 *
## op_count:arg2 0.0778466 0.0011877 65.546 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1603 on 579 degrees of freedom
## Multiple R-squared: 0.9789, Adjusted R-squared: 0.9786
## F-statistic: 3832 on 7 and 579 DF, p-value: < 0.00000000000000022
##
## [1] "RETURNDATACOPY" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -896.42 -47.24 -1.40 57.80 633.85
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10829.300727383 23.405280309 462.686 < 0.0000000000000002 ***
## op_count 23.179662277 1.200366550 19.310 < 0.0000000000000002 ***
## arg0 0.000778439 0.001847385 0.421 0.67364
## arg1 0.000044220 0.001691335 0.026 0.97915
## arg2 0.001502633 0.001639579 0.916 0.35979
## op_count:arg0 0.000002035 0.000094607 0.022 0.98285
## op_count:arg1 -0.000238311 0.000086719 -2.748 0.00618 **
## op_count:arg2 0.006399083 0.000084410 75.810 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 121.8 on 586 degrees of freedom
## Multiple R-squared: 0.9875, Adjusted R-squared: 0.9873
## F-statistic: 6603 on 7 and 586 DF, p-value: < 0.00000000000000022
##
## [1] "DIV" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -690.25 -155.33 -45.25 121.05 939.35
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16148.1765 27.1826 594.064 < 0.0000000000000002 ***
## op_count 8.5062 0.9519 8.937 < 0.0000000000000002 ***
## arg0 3.2145 1.1446 2.808 0.00515 **
## arg1 4.4483 1.1080 4.015 0.0000673 ***
## op_count:expensiveTRUE 17.2494 1.2086 14.272 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 220 on 581 degrees of freedom
## Multiple R-squared: 0.6018, Adjusted R-squared: 0.5991
## F-statistic: 219.5 on 4 and 581 DF, p-value: < 0.00000000000000022
##
## [1] "MOD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -642.79 -160.24 -43.83 129.07 1183.75
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16173.9560 27.3053 592.337 < 0.0000000000000002 ***
## op_count 11.2225 0.9838 11.407 < 0.0000000000000002 ***
## arg0 3.7276 1.1380 3.276 0.00112 **
## arg1 2.8072 1.1426 2.457 0.01431 *
## op_count:expensiveTRUE 15.2856 1.2184 12.546 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 220.7 on 588 degrees of freedom
## Multiple R-squared: 0.6277, Adjusted R-squared: 0.6251
## F-statistic: 247.8 on 4 and 588 DF, p-value: < 0.00000000000000022
##
## [1] "SDIV" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -628.5 -149.0 -36.4 133.9 867.8
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16171.1205 25.0433 645.727 < 0.0000000000000002 ***
## op_count 10.1455 0.8976 11.303 < 0.0000000000000002 ***
## arg0 1.4356 1.0832 1.325 0.186
## arg1 4.7527 1.0587 4.489 0.00000862 ***
## op_count:expensiveTRUE 18.4079 1.1306 16.282 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 204.7 on 585 degrees of freedom
## Multiple R-squared: 0.6739, Adjusted R-squared: 0.6717
## F-statistic: 302.3 on 4 and 585 DF, p-value: < 0.00000000000000022
##
## [1] "SMOD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -565.79 -160.52 -33.96 116.68 1115.42
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16170.828 27.229 593.882 < 0.0000000000000002 ***
## op_count 12.692 0.916 13.856 < 0.0000000000000002 ***
## arg0 4.781 1.110 4.307 0.0000194 ***
## arg1 3.067 1.161 2.643 0.00844 **
## op_count:expensiveTRUE 14.101 1.193 11.823 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 217.7 on 584 degrees of freedom
## Multiple R-squared: 0.6272, Adjusted R-squared: 0.6247
## F-statistic: 245.6 on 4 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "ADDMOD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -706.88 -148.44 -33.84 124.20 827.18
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16157.8184 32.7485 493.391 < 0.0000000000000002 ***
## op_count 9.6589 1.1662 8.282 0.000000000000000845 ***
## arg0 1.5244 0.9668 1.577 0.1154
## arg1 2.2301 1.0087 2.211 0.0274 *
## arg2 5.0316 1.1075 4.543 0.000006747026021407 ***
## op_count:expensiveTRUE 22.6996 1.2428 18.265 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 212.5 on 577 degrees of freedom
## Multiple R-squared: 0.7613, Adjusted R-squared: 0.7592
## F-statistic: 368.1 on 5 and 577 DF, p-value: < 0.00000000000000022
##
## [1] "MULMOD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -548.67 -172.90 -37.49 149.47 895.24
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15914.482 34.362 463.141 < 0.0000000000000002 ***
## op_count 27.223 1.538 17.698 < 0.0000000000000002 ***
## arg0 8.560 1.109 7.718 0.00000000000005120 ***
## arg1 9.025 1.126 8.015 0.00000000000000598 ***
## arg2 5.302 1.150 4.611 0.00000492957174872 ***
## op_count:expensiveTRUE 22.017 1.588 13.864 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 243.7 on 586 degrees of freedom
## Multiple R-squared: 0.8591, Adjusted R-squared: 0.8579
## F-statistic: 714.4 on 5 and 586 DF, p-value: < 0.00000000000000022proceed_with_opcodes = unique(first_pass[which(first_pass$has_impacting == 'TRUE'), 'opcode'])
models_with_args_automatic = first_pass[which(first_pass$has_impacting == 'TRUE'), c('opcode', 'env')]
models_with_expensive_automatic = first_pass[which(!is.na(first_pass$expensive_ns)), c('opcode', 'env')]
first_pass[which(first_pass$has_impacting == 'TRUE'), ]## opcode env has_significant has_impacting estimate_marginal_ns
## 30 EXP erigon TRUE TRUE -11.7862332200797
## 64 CALLDATACOPY erigon TRUE TRUE 26.6003432650516
## 65 CODECOPY erigon TRUE TRUE 54.7746243825654
## 66 RETURNDATACOPY erigon TRUE TRUE 23.1796622773222
## arg0_ns arg1_ns arg2_ns expensive_ns
## 30 <NA> 84.5864820819063 <NA> <NA>
## 64 <NA> <NA> 0.00653350024119791 <NA>
## 65 <NA> <NA> 0.077846565141782 <NA>
## 66 <NA> <NA> 0.00639908331644716 <NA>
## arg0_ns_raw arg1_ns_raw arg2_ns_raw
## 30 0.593262643575804 84.5864820819063 <NA>
## 64 0.0000157133969121786 -0.0000711858620834852 0.00653350024119791
## 65 0.000465412658995019 -0.0023436936566968 0.077846565141782
## 66 0.0000020346686465009 -0.000238311229402693 0.00639908331644716
## expensive_ns_raw arg0_ns_p arg1_ns_p arg2_ns_p
## 30 <NA> 0.035706546802898 0 <NA>
## 64 <NA> 0.873139605947461 0.486776480835768 6.76577189126993e-286
## 65 <NA> 0.690770961246267 0.0428673956143399 4.63858082465433e-270
## 66 <NA> 0.982848941186765 0.00617881113902434 4.55971679853581e-305
## expensive_ns_p
## 30 <NA>
## 64 <NA>
## 65 <NA>
## 66 <NA>We inspect the automatic choice of models, but then coerce the choice
to a fixed list. We drop the division OPCODEs (DIV etc.),
because their arguments only seem to have an indirect impact via the
fact that x / y is trivial if x < y. This makes the
DIV(x, y) appear costlier for large x and cheaper for large
y.
models_with_args = data.frame(opcode="EXP", env=env, arg=1)
first_pass$arg1_ns[is.na(first_pass$arg1_ns) & first_pass$opcode=="EXP" & first_pass$env==env] <- first_pass$arg1_ns_raw[is.na(first_pass$arg1_ns) & first_pass$opcode=="EXP" & first_pass$env==env]
models_with_args = rbind(models_with_args, data.frame(opcode="CALLDATACOPY", env=env, arg=2))
first_pass$arg2_ns[is.na(first_pass$arg2_ns) & first_pass$opcode=="CALLDATACOPY" & first_pass$env==env] <- first_pass$arg2_ns_raw[is.na(first_pass$arg2_ns) & first_pass$opcode=="CALLDATACOPY" & first_pass$env==env]
models_with_args = rbind(models_with_args, data.frame(opcode="CODECOPY", env=env, arg=2))
first_pass$arg2_ns[is.na(first_pass$arg2_ns) & first_pass$opcode=="CODECOPY" & first_pass$env==env] <- first_pass$arg2_ns_raw[is.na(first_pass$arg2_ns) & first_pass$opcode=="CODECOPY" & first_pass$env==env]
models_with_args = rbind(models_with_args, data.frame(opcode="RETURNDATACOPY", env=env, arg=2))
first_pass$arg2_ns[is.na(first_pass$arg2_ns) & first_pass$opcode=="RETURNDATACOPY" & first_pass$env==env] <- first_pass$arg2_ns_raw[is.na(first_pass$arg2_ns) & first_pass$opcode=="RETURNDATACOPY" & first_pass$env==env]
models_with_expensive = data.frame(opcode="DIV", env=env)
models_with_expensive = rbind(models_with_expensive, data.frame(opcode="SDIV", env=env))
models_with_expensive = rbind(models_with_expensive, data.frame(opcode="MOD", env=env))
models_with_expensive = rbind(models_with_expensive, data.frame(opcode="SMOD", env=env))
models_with_expensive = rbind(models_with_expensive, data.frame(opcode="ADDMOD", env=env))
models_with_expensive = rbind(models_with_expensive, data.frame(opcode="MULMOD", env=env))Detailed analysis for selected OPCODEs
We go through all the OPCODEs which turned out to have impacting arguments in the automatic discrimination procedure, and we plot some validation plots to inspect these relationships.
# Takes the results data frame and checks which argument indices (0, 1, etc.)
# turned out to be impacting
get_impact_args_for <- function(df, opcode, env) {
if (opcode %in% nullary_opcodes) {
return(c())
}
args = c()
for (n in 0:2) {
argname = paste0('arg', n, '_ns')
if (!is.na(df[which(df$opcode==opcode & df$env==env), argname])) {
args = c(n, args)
}
}
return(rev(args))
}
# same as `get_impact_args_for` but gets all the argument indices
get_args_for <- function(df, opcode, env) {
if (opcode %in% unary_opcodes) {
c(0)
} else if (opcode %in% binary_opcodes) {
c(0, 1)
} else if (opcode %in% ternary_opcodes) {
c(0, 1, 2)
}
}
# Builds a final model formula to estimate, based on whether the arguments
# came out impactful from the automatic discrimination process.
get_model_formula_for <- function(df, opcode, env) {
args = get_args_for(df, opcode, env)
argnames = paste0('arg', args)
args_formula = paste0(argnames, collapse=' + ')
impact_args = get_impact_args_for(df, opcode, env)
if (opcode %in% nullary_opcodes) {
as.formula('measure_total_time_ns ~ op_count')
} else if (is.null(impact_args)) {
as.formula(paste0('measure_total_time_ns ~ op_count + ', args_formula))
} else {
arg_op_count_names = paste0('arg', impact_args, ':op_count')
arg_op_counts_formula = paste0(arg_op_count_names, collapse=' + ')
as.formula(paste0('measure_total_time_ns ~ op_count + ', args_formula, ' + ', arg_op_counts_formula))
}
}
# Same as `get_model_formula_for` but gauged towards the division OPCODEs specifically.
get_expensive_model_formula_for <- function(df, opcode, env) {
args = get_args_for(df, opcode, env)
argnames = paste0('arg', args)
args_formula = paste0(argnames, collapse=' + ')
as.formula(paste0('measure_total_time_ns ~ op_count + ', args_formula, ' + expensive:op_count'))
}
# Same as `get_model_formula_for` but returns the formula to provide the `aggregate` function with.
get_aggregate_formula_for <- function(df, opcode, env) {
args = get_args_for(df, opcode, env)
argnames = paste0('arg', args)
args_formula = paste0(argnames, collapse=' * ')
as.formula(paste0('measure_total_time_ns ~ op_count * env * opcode * ', args_formula))
}
# Presents the diagnostic plots for a given slice of the data
plot_model <- function(df, opcode, env, use_mean) {
if (missing(use_mean)) {
use_mean = FALSE
}
if (use_mean) {
df = aggregate(get_aggregate_formula_for(df, opcode, env), measurements[which(df$opcode==opcode & df$env==env), ], mean, na.action=na.pass)
}
model = arg_lm(df, opcode, env, get_model_formula_for(first_pass, opcode, env))
print(c(opcode, env))
print(summary(model))
par(mfrow=c(2,2))
plot(model)
plot_data = df[which(df$env == env & df$opcode == opcode & df$op_count == max(df$op_count)), ]
if (opcode %in% binary_opcodes) {
par(mfrow=c(1,1))
decreasing_colors = heat.colors(nrow(plot_data))
plot_data=plot_data[order(plot_data$measure_total_time_ns, decreasing=TRUE), ]
with(plot_data, plot(arg0, arg1, col=decreasing_colors, pch=19))
}
title(main=paste(opcode, env))
}Using the functions defined above, we proceed to plot the diagnostic plots of the arguments models.
for (env in all_envs) {
for (opcode in proceed_with_opcodes) {
plot_model(measurements, opcode, env, use_mean=TRUE)
}
}## [1] "EXP" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4077.4 -245.2 -12.1 323.1 4417.7
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16144.7165 118.9356 135.743 <0.0000000000000002 ***
## op_count -4.5829 5.4225 -0.845 0.3984
## arg0 7.2177 3.6817 1.960 0.0505 .
## arg1 0.1519 5.6195 0.027 0.9784
## op_count:arg1 84.7828 0.2877 294.673 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 784.1 on 520 degrees of freedom
## Multiple R-squared: 0.9989, Adjusted R-squared: 0.9989
## F-statistic: 1.148e+05 on 4 and 520 DF, p-value: < 0.00000000000000022
## [1] "CALLDATACOPY" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1088.98 -65.59 -4.76 67.56 523.49
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8118.94103512 21.97443561 369.472 <0.0000000000000002 ***
## op_count 26.10770054 0.88614861 29.462 <0.0000000000000002 ***
## arg0 0.00070090 0.00119979 0.584 0.559
## arg1 -0.00191273 0.00124570 -1.535 0.125
## arg2 0.00230160 0.00181878 1.265 0.206
## op_count:arg2 0.00653902 0.00009309 70.246 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 136.4 on 587 degrees of freedom
## Multiple R-squared: 0.9864, Adjusted R-squared: 0.9863
## F-statistic: 8528 on 5 and 587 DF, p-value: < 0.00000000000000022
## [1] "CODECOPY" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5353.6 -384.8 5.8 373.6 8717.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 11128.333747 279.031979 39.882 < 0.0000000000000002 ***
## op_count 37.077841 11.023932 3.363 0.000821 ***
## arg0 0.005690 0.014259 0.399 0.689993
## arg1 -0.034010 0.014088 -2.414 0.016079 *
## arg2 -0.002619 0.023203 -0.113 0.910179
## op_count:arg2 0.078175 0.001178 66.350 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1606 on 581 degrees of freedom
## Multiple R-squared: 0.9787, Adjusted R-squared: 0.9785
## F-statistic: 5340 on 5 and 581 DF, p-value: < 0.00000000000000022
## [1] "RETURNDATACOPY" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -898.97 -47.97 -2.43 58.42 656.85
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10857.60063996 18.94033436 573.253 < 0.0000000000000002 ***
## op_count 21.32970274 0.79346680 26.882 < 0.0000000000000002 ***
## arg0 0.00075991 0.00115888 0.656 0.512256
## arg1 -0.00358380 0.00106296 -3.372 0.000797 ***
## arg2 0.00161308 0.00164519 0.980 0.327251
## op_count:arg2 0.00639264 0.00008464 75.528 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 122.3 on 588 degrees of freedom
## Multiple R-squared: 0.9873, Adjusted R-squared: 0.9872
## F-statistic: 9155 on 5 and 588 DF, p-value: < 0.00000000000000022
Producing the final estimates
We’d like to only estimate using the arg-variables in models, where this actually matters to avoid spurious impact of insignificant variables.
We’ll estimate a model with only those argument variables, where they turned out impacting. For those where no argument variable was impacting, we’ll only estimate the marginal increase (corresponding to the constant cost of an OPCODE).
# `results_df` is assumed to have the columns as the `estimates` data frame has (see below)
add_non_arg_model_estimates <- function(model, results_df, env, opcode) {
pure_op_count_coeff = summary(model)$coefficients["op_count", 1]
args_ns = c(NA, NA, NA)
args_ns_stderr = c(NA, NA, NA)
results_df[nrow(results_df) + 1, ] = c(opcode, env, FALSE, FALSE, pure_op_count_coeff, args_ns, NA, args_ns_stderr, NA)
return(results_df)
}
add_arg_model_estimates <- function(model, opcode, env, results_df, df) {
all_coefficients = summary(model)$coefficients
arg_coefficients = all_coefficients[!(row.names(all_coefficients) %in% c("op_count", "(Intercept)", "arg0", "arg1", "arg2")),]
pure_op_count_coeff = all_coefficients["op_count", 1]
# will be filled if any is impacting
args_ns = c(NA, NA, NA)
args_ns_stderr = c(NA, NA, NA)
impact_args = get_impact_args_for(df, opcode, env)
arg_op_count_names = paste0('op_count:arg', impact_args)
args_ns[impact_args + 1] = all_coefficients[arg_op_count_names, 'Estimate']
args_ns_stderr[impact_args + 1] = all_coefficients[arg_op_count_names, 'Std. Error']
results_df[nrow(results_df) + 1, ] = c(opcode, env, TRUE, TRUE, pure_op_count_coeff, args_ns, NA, args_ns_stderr, NA)
return(results_df)
}
add_expensive_model_estimates <- function(model, opcode, env, results_df, df) {
all_coefficients = summary(model)$coefficients
pure_op_count_coeff = all_coefficients["op_count", 1]
args_ns = c(NA, NA, NA)
args_ns_stderr = c(NA, NA, NA)
expensive = all_coefficients['op_count:expensiveTRUE', 'Estimate']
expensive_stderr = all_coefficients['op_count:expensiveTRUE', 'Std. Error']
results_df[nrow(results_df) + 1, ] = c(opcode, env, TRUE, TRUE, pure_op_count_coeff, args_ns, expensive, args_ns_stderr, expensive_stderr)
return(results_df)
}estimates = data.frame(matrix(ncol = 13, nrow = 0))
colnames(estimates) <- c('opcode', 'env', 'has_significant', 'has_impacting', 'estimate_marginal_ns',
'arg0_ns', 'arg1_ns', 'arg2_ns', 'expensive_ns', 'arg0_ns_stderr', 'arg1_ns_stderr', 'arg2_ns_stderr', 'expensive_ns_stderr')
for (env in all_envs) {
for (opcode in all_opcodes) {
is_modeled_with_args = nrow(merge(data.frame(opcode=opcode, env=env), models_with_args)) > 0
is_modeled_with_expensive = nrow(merge(data.frame(opcode=opcode, env=env), models_with_expensive)) > 0
if (is_modeled_with_expensive) {
model = arg_lm(measurements, opcode, env, get_expensive_model_formula_for(first_pass, opcode, env))
estimates = add_expensive_model_estimates(model, opcode, env, estimates, first_pass)
} else if (is_modeled_with_args) {
model = arg_lm(measurements, opcode, env, get_model_formula_for(first_pass, opcode, env))
estimates = add_arg_model_estimates(model, opcode, env, estimates, first_pass)
} else {
model = arg_lm(measurements, opcode, env, get_model_formula_for(first_pass, opcode, env))
estimates = add_non_arg_model_estimates(model, estimates, env, opcode)
}
print(c(opcode, env))
print(summary(model))
}
}## [1] "ADD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -252.01 -132.37 -48.27 91.65 530.83
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16243.37692 20.90860 776.876 <0.0000000000000002 ***
## op_count 6.68006 0.55118 12.120 <0.0000000000000002 ***
## arg0 1.15853 0.75310 1.538 0.125
## arg1 0.09315 0.73625 0.127 0.899
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 162 on 569 degrees of freedom
## Multiple R-squared: 0.2078, Adjusted R-squared: 0.2037
## F-statistic: 49.77 on 3 and 569 DF, p-value: < 0.00000000000000022
##
## [1] "MUL" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -252.36 -136.89 -60.46 99.78 557.87
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16317.7592 21.6514 753.660 <0.0000000000000002 ***
## op_count 7.8166 0.5761 13.569 <0.0000000000000002 ***
## arg0 -1.1725 0.7894 -1.485 0.138
## arg1 -0.4097 0.7960 -0.515 0.607
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 170.4 on 570 degrees of freedom
## Multiple R-squared: 0.2459, Adjusted R-squared: 0.2419
## F-statistic: 61.95 on 3 and 570 DF, p-value: < 0.00000000000000022
##
## [1] "SUB" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -246.45 -154.97 -53.54 106.30 588.16
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16320.1267 23.2655 701.473 <0.0000000000000002 ***
## op_count 5.2397 0.6169 8.494 <0.0000000000000002 ***
## arg0 0.1816 0.8452 0.215 0.830
## arg1 -0.8082 0.8373 -0.965 0.335
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 181.6 on 578 degrees of freedom
## Multiple R-squared: 0.1124, Adjusted R-squared: 0.1077
## F-statistic: 24.39 on 3 and 578 DF, p-value: 0.000000000000007173
##
## [1] "DIV" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -690.25 -155.33 -45.25 121.05 939.35
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16148.1765 27.1826 594.064 < 0.0000000000000002 ***
## op_count 8.5062 0.9519 8.937 < 0.0000000000000002 ***
## arg0 3.2145 1.1446 2.808 0.00515 **
## arg1 4.4483 1.1080 4.015 0.0000673 ***
## op_count:expensiveTRUE 17.2494 1.2086 14.272 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 220 on 581 degrees of freedom
## Multiple R-squared: 0.6018, Adjusted R-squared: 0.5991
## F-statistic: 219.5 on 4 and 581 DF, p-value: < 0.00000000000000022
##
## [1] "SDIV" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -628.5 -149.0 -36.4 133.9 867.8
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16171.1205 25.0433 645.727 < 0.0000000000000002 ***
## op_count 10.1455 0.8976 11.303 < 0.0000000000000002 ***
## arg0 1.4356 1.0832 1.325 0.186
## arg1 4.7527 1.0587 4.489 0.00000862 ***
## op_count:expensiveTRUE 18.4079 1.1306 16.282 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 204.7 on 585 degrees of freedom
## Multiple R-squared: 0.6739, Adjusted R-squared: 0.6717
## F-statistic: 302.3 on 4 and 585 DF, p-value: < 0.00000000000000022
##
## [1] "MOD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -642.79 -160.24 -43.83 129.07 1183.75
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16173.9560 27.3053 592.337 < 0.0000000000000002 ***
## op_count 11.2225 0.9838 11.407 < 0.0000000000000002 ***
## arg0 3.7276 1.1380 3.276 0.00112 **
## arg1 2.8072 1.1426 2.457 0.01431 *
## op_count:expensiveTRUE 15.2856 1.2184 12.546 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 220.7 on 588 degrees of freedom
## Multiple R-squared: 0.6277, Adjusted R-squared: 0.6251
## F-statistic: 247.8 on 4 and 588 DF, p-value: < 0.00000000000000022
##
## [1] "SMOD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -565.79 -160.52 -33.96 116.68 1115.42
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16170.828 27.229 593.882 < 0.0000000000000002 ***
## op_count 12.692 0.916 13.856 < 0.0000000000000002 ***
## arg0 4.781 1.110 4.307 0.0000194 ***
## arg1 3.067 1.161 2.643 0.00844 **
## op_count:expensiveTRUE 14.101 1.193 11.823 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 217.7 on 584 degrees of freedom
## Multiple R-squared: 0.6272, Adjusted R-squared: 0.6247
## F-statistic: 245.6 on 4 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "ADDMOD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -706.88 -148.44 -33.84 124.20 827.18
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16157.8184 32.7485 493.391 < 0.0000000000000002 ***
## op_count 9.6589 1.1662 8.282 0.000000000000000845 ***
## arg0 1.5244 0.9668 1.577 0.1154
## arg1 2.2301 1.0087 2.211 0.0274 *
## arg2 5.0316 1.1075 4.543 0.000006747026021407 ***
## op_count:expensiveTRUE 22.6996 1.2428 18.265 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 212.5 on 577 degrees of freedom
## Multiple R-squared: 0.7613, Adjusted R-squared: 0.7592
## F-statistic: 368.1 on 5 and 577 DF, p-value: < 0.00000000000000022
##
## [1] "MULMOD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -548.67 -172.90 -37.49 149.47 895.24
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15914.482 34.362 463.141 < 0.0000000000000002 ***
## op_count 27.223 1.538 17.698 < 0.0000000000000002 ***
## arg0 8.560 1.109 7.718 0.00000000000005120 ***
## arg1 9.025 1.126 8.015 0.00000000000000598 ***
## arg2 5.302 1.150 4.611 0.00000492957174872 ***
## op_count:expensiveTRUE 22.017 1.588 13.864 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 243.7 on 586 degrees of freedom
## Multiple R-squared: 0.8591, Adjusted R-squared: 0.8579
## F-statistic: 714.4 on 5 and 586 DF, p-value: < 0.00000000000000022
##
## [1] "EXP" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4042.2 -249.7 -6.6 312.3 4444.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16118.9838 111.5794 144.462 <0.0000000000000002 ***
## op_count -2.9448 5.0916 -0.578 0.5632
## arg0 8.2461 3.4427 2.395 0.0169 *
## arg1 0.6358 5.2652 0.121 0.9039
## op_count:arg1 84.6379 0.2699 313.611 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 785.7 on 589 degrees of freedom
## Multiple R-squared: 0.9989, Adjusted R-squared: 0.9989
## F-statistic: 1.295e+05 on 4 and 589 DF, p-value: < 0.00000000000000022
##
## [1] "SIGNEXTEND" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -268.54 -124.79 -55.65 96.34 491.13
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16305.7081 18.8128 866.734 <0.0000000000000002 ***
## op_count 6.8671 0.5243 13.099 <0.0000000000000002 ***
## arg0 -1.1152 0.6822 -1.635 0.103
## arg1 -1.0518 0.7045 -1.493 0.136
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 154.7 on 576 degrees of freedom
## Multiple R-squared: 0.2349, Adjusted R-squared: 0.2309
## F-statistic: 58.93 on 3 and 576 DF, p-value: < 0.00000000000000022
##
## [1] "LT" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -214.87 -119.74 -55.89 95.30 459.77
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16298.4241 19.8327 821.796 <0.0000000000000002 ***
## op_count 6.7176 0.5248 12.799 <0.0000000000000002 ***
## arg0 -1.3014 0.7152 -1.820 0.0693 .
## arg1 -1.3473 0.7357 -1.831 0.0676 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 153.7 on 566 degrees of freedom
## Multiple R-squared: 0.2317, Adjusted R-squared: 0.2276
## F-statistic: 56.89 on 3 and 566 DF, p-value: < 0.00000000000000022
##
## [1] "GT" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -228.29 -124.95 -46.68 90.74 535.76
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16292.2600 20.0245 813.616 <0.0000000000000002 ***
## op_count 5.5180 0.5479 10.071 <0.0000000000000002 ***
## arg0 -0.1873 0.7727 -0.242 0.809
## arg1 -0.4106 0.7411 -0.554 0.580
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 161 on 571 degrees of freedom
## Multiple R-squared: 0.1511, Adjusted R-squared: 0.1467
## F-statistic: 33.89 on 3 and 571 DF, p-value: < 0.00000000000000022
##
## [1] "SLT" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -248.5 -135.7 -60.1 102.0 532.5
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16252.1043 22.6334 718.058 <0.0000000000000002 ***
## op_count 8.5406 0.5742 14.875 <0.0000000000000002 ***
## arg0 1.1854 0.7781 1.523 0.128
## arg1 0.1455 0.7541 0.193 0.847
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 169.6 on 574 degrees of freedom
## Multiple R-squared: 0.2802, Adjusted R-squared: 0.2765
## F-statistic: 74.49 on 3 and 574 DF, p-value: < 0.00000000000000022
##
## [1] "SGT" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -248.2 -139.3 -45.3 108.5 533.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16293.96862 21.51939 757.176 <0.0000000000000002 ***
## op_count 8.46449 0.58250 14.531 <0.0000000000000002 ***
## arg0 -0.01733 0.84569 -0.020 0.984
## arg1 -0.94348 0.76030 -1.241 0.215
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 172.7 on 582 degrees of freedom
## Multiple R-squared: 0.2681, Adjusted R-squared: 0.2644
## F-statistic: 71.08 on 3 and 582 DF, p-value: < 0.00000000000000022
##
## [1] "EQ" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -225.64 -126.37 -63.68 97.43 515.47
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16278.3642 20.5879 790.676 <0.0000000000000002 ***
## op_count 6.1242 0.5602 10.932 <0.0000000000000002 ***
## arg0 -0.9902 0.7443 -1.330 0.184
## arg1 -0.3152 0.7826 -0.403 0.687
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 165.1 on 568 degrees of freedom
## Multiple R-squared: 0.1765, Adjusted R-squared: 0.1721
## F-statistic: 40.57 on 3 and 568 DF, p-value: < 0.00000000000000022
##
## [1] "ISZERO" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -261.18 -127.02 -51.76 98.03 484.70
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16252.3261 15.7026 1035.007 < 0.0000000000000002 ***
## op_count 3.9173 0.5535 7.078 0.00000000000429 ***
## arg0 1.9954 0.7490 2.664 0.00794 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 162.3 on 574 degrees of freedom
## Multiple R-squared: 0.09066, Adjusted R-squared: 0.08749
## F-statistic: 28.61 on 2 and 574 DF, p-value: 0.000000000001429
##
## [1] "AND" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -250.55 -133.75 -53.81 90.87 543.94
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16308.0684 20.3374 801.876 <0.0000000000000002 ***
## op_count 5.1930 0.5716 9.084 <0.0000000000000002 ***
## arg0 -1.0173 0.7424 -1.370 0.171
## arg1 -0.3341 0.7977 -0.419 0.675
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 168.7 on 573 degrees of freedom
## Multiple R-squared: 0.1285, Adjusted R-squared: 0.1239
## F-statistic: 28.16 on 3 and 573 DF, p-value: < 0.00000000000000022
##
## [1] "OR" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -255.10 -131.63 -44.71 100.08 506.81
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16236.9775 20.3395 798.299 <0.0000000000000002 ***
## op_count 6.3259 0.5574 11.348 <0.0000000000000002 ***
## arg0 0.3520 0.7514 0.468 0.6397
## arg1 1.6078 0.7489 2.147 0.0322 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 163.8 on 576 degrees of freedom
## Multiple R-squared: 0.188, Adjusted R-squared: 0.1838
## F-statistic: 44.45 on 3 and 576 DF, p-value: < 0.00000000000000022
##
## [1] "XOR" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -284.23 -129.03 -37.26 100.80 583.99
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16314.8813 20.0609 813.268 < 0.0000000000000002 ***
## op_count 3.6543 0.5619 6.504 0.000000000171 ***
## arg0 -1.1649 0.7303 -1.595 0.111
## arg1 0.8139 0.7347 1.108 0.268
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 165.3 on 572 degrees of freedom
## Multiple R-squared: 0.07421, Adjusted R-squared: 0.06936
## F-statistic: 15.28 on 3 and 572 DF, p-value: 0.000000001405
##
## [1] "NOT" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -224.68 -124.83 -59.20 88.96 491.09
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16284.3867 16.7215 973.858 < 0.0000000000000002 ***
## op_count 4.1444 0.5549 7.469 0.000000000000301 ***
## arg0 -0.8649 0.7410 -1.167 0.244
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 163.1 on 576 degrees of freedom
## Multiple R-squared: 0.09056, Adjusted R-squared: 0.0874
## F-statistic: 28.68 on 2 and 576 DF, p-value: 0.000000000001339
##
## [1] "BYTE" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -235.90 -132.42 -56.77 91.11 515.73
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16303.9836 22.0164 740.538 <0.0000000000000002 ***
## op_count 6.7323 0.5782 11.643 <0.0000000000000002 ***
## arg0 -1.6801 0.8016 -2.096 0.0365 *
## arg1 -0.7858 0.7858 -1.000 0.3177
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 169.5 on 575 degrees of freedom
## Multiple R-squared: 0.196, Adjusted R-squared: 0.1919
## F-statistic: 46.74 on 3 and 575 DF, p-value: < 0.00000000000000022
##
## [1] "SHL" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -258.76 -129.46 -49.02 96.19 511.17
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16276.7124 19.9246 816.914 < 0.0000000000000002 ***
## op_count 4.3669 0.5552 7.866 0.0000000000000185 ***
## arg0 0.5461 0.7236 0.755 0.451
## arg1 -0.1370 0.7476 -0.183 0.855
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 163.1 on 570 degrees of freedom
## Multiple R-squared: 0.09936, Adjusted R-squared: 0.09462
## F-statistic: 20.96 on 3 and 570 DF, p-value: 0.0000000000006797
##
## [1] "SHR" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -237.22 -132.09 -59.82 100.91 534.06
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16275.7533 19.3626 840.578 <0.0000000000000002 ***
## op_count 5.8321 0.5621 10.376 <0.0000000000000002 ***
## arg0 -1.2941 0.7577 -1.708 0.0882 .
## arg1 0.7860 0.7495 1.049 0.2948
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 166.3 on 575 degrees of freedom
## Multiple R-squared: 0.1626, Adjusted R-squared: 0.1583
## F-statistic: 37.23 on 3 and 575 DF, p-value: < 0.00000000000000022
##
## [1] "SAR" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -264.98 -134.53 -58.23 102.12 552.30
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16282.7814 22.9020 710.976 <0.0000000000000002 ***
## op_count 5.5809 0.5834 9.566 <0.0000000000000002 ***
## arg0 -0.6232 0.8050 -0.774 0.4391
## arg1 1.4937 0.7976 1.873 0.0616 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 173 on 581 degrees of freedom
## Multiple R-squared: 0.1416, Adjusted R-squared: 0.1372
## F-statistic: 31.96 on 3 and 581 DF, p-value: < 0.00000000000000022
##
## [1] "ADDRESS" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -157.381 -58.472 -7.836 42.710 228.528
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4165.2901 4.9424 842.76 <0.0000000000000002 ***
## op_count 19.4061 0.2542 76.33 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 75.79 on 588 degrees of freedom
## Multiple R-squared: 0.9083, Adjusted R-squared: 0.9082
## F-statistic: 5826 on 1 and 588 DF, p-value: < 0.00000000000000022
##
## [1] "ORIGIN" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -153.690 -52.746 -7.492 43.707 230.707
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4184.6899 4.4914 931.71 <0.0000000000000002 ***
## op_count 10.4402 0.2326 44.88 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 68.99 on 584 degrees of freedom
## Multiple R-squared: 0.7753, Adjusted R-squared: 0.7749
## F-statistic: 2014 on 1 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "CALLER" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -155.85 -48.85 -12.85 45.26 257.26
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4183.8472 4.5614 917.23 <0.0000000000000002 ***
## op_count 9.5263 0.2371 40.18 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 69.51 on 578 degrees of freedom
## Multiple R-squared: 0.7363, Adjusted R-squared: 0.7359
## F-statistic: 1614 on 1 and 578 DF, p-value: < 0.00000000000000022
##
## [1] "CALLVALUE" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -147.89 -59.35 -13.53 49.79 247.83
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4173.8931 5.2991 787.66 <0.0000000000000002 ***
## op_count 5.0425 0.2731 18.46 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 81.22 on 585 degrees of freedom
## Multiple R-squared: 0.3681, Adjusted R-squared: 0.3671
## F-statistic: 340.8 on 1 and 585 DF, p-value: < 0.00000000000000022
##
## [1] "CALLDATALOAD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -145.67 -41.03 -11.48 37.65 175.04
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9262.3361755 5.9206208 1564.420 <0.0000000000000002 ***
## op_count 6.8162980 0.2014758 33.832 <0.0000000000000002 ***
## arg0 0.0003159 0.0005089 0.621 0.535
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 59.3 on 579 degrees of freedom
## Multiple R-squared: 0.6642, Adjusted R-squared: 0.6631
## F-statistic: 572.7 on 2 and 579 DF, p-value: < 0.00000000000000022
##
## [1] "CALLDATASIZE" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -161.326 -56.326 -9.475 50.525 245.824
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4172.4753 5.2160 799.94 <0.0000000000000002 ***
## op_count 5.7234 0.2689 21.29 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 79.45 on 575 degrees of freedom
## Multiple R-squared: 0.4407, Adjusted R-squared: 0.4397
## F-statistic: 453.1 on 1 and 575 DF, p-value: < 0.00000000000000022
##
## [1] "CALLDATACOPY" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1088.98 -65.59 -4.76 67.56 523.49
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8118.94103512 21.97443561 369.472 <0.0000000000000002 ***
## op_count 26.10770054 0.88614861 29.462 <0.0000000000000002 ***
## arg0 0.00070090 0.00119979 0.584 0.559
## arg1 -0.00191273 0.00124570 -1.535 0.125
## arg2 0.00230160 0.00181878 1.265 0.206
## op_count:arg2 0.00653902 0.00009309 70.246 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 136.4 on 587 degrees of freedom
## Multiple R-squared: 0.9864, Adjusted R-squared: 0.9863
## F-statistic: 8528 on 5 and 587 DF, p-value: < 0.00000000000000022
##
## [1] "CODESIZE" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -153.438 -61.993 -7.382 53.590 245.118
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4178.3270 5.3710 777.94 <0.0000000000000002 ***
## op_count 5.8370 0.2765 21.11 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 82.42 on 590 degrees of freedom
## Multiple R-squared: 0.4304, Adjusted R-squared: 0.4294
## F-statistic: 445.7 on 1 and 590 DF, p-value: < 0.00000000000000022
##
## [1] "CODECOPY" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -5353.6 -384.8 5.8 373.6 8717.6
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 11128.333747 279.031979 39.882 < 0.0000000000000002 ***
## op_count 37.077841 11.023932 3.363 0.000821 ***
## arg0 0.005690 0.014259 0.399 0.689993
## arg1 -0.034010 0.014088 -2.414 0.016079 *
## arg2 -0.002619 0.023203 -0.113 0.910179
## op_count:arg2 0.078175 0.001178 66.350 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1606 on 581 degrees of freedom
## Multiple R-squared: 0.9787, Adjusted R-squared: 0.9785
## F-statistic: 5340 on 5 and 581 DF, p-value: < 0.00000000000000022
##
## [1] "GASPRICE" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -166.89 -62.56 -10.89 49.11 237.11
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4178.5599 5.4342 768.94 <0.0000000000000002 ***
## op_count 6.1776 0.2795 22.11 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 82.36 on 577 degrees of freedom
## Multiple R-squared: 0.4585, Adjusted R-squared: 0.4576
## F-statistic: 488.6 on 1 and 577 DF, p-value: < 0.00000000000000022
##
## [1] "RETURNDATASIZE" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -145.311 -56.311 -6.811 47.403 219.403
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4175.0254 4.8503 860.77 <0.0000000000000002 ***
## op_count 5.0857 0.2513 20.24 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 74.04 on 574 degrees of freedom
## Multiple R-squared: 0.4165, Adjusted R-squared: 0.4155
## F-statistic: 409.7 on 1 and 574 DF, p-value: < 0.00000000000000022
##
## [1] "RETURNDATACOPY" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -898.97 -47.97 -2.43 58.42 656.85
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10857.60063996 18.94033436 573.253 < 0.0000000000000002 ***
## op_count 21.32970274 0.79346680 26.882 < 0.0000000000000002 ***
## arg0 0.00075991 0.00115888 0.656 0.512256
## arg1 -0.00358380 0.00106296 -3.372 0.000797 ***
## arg2 0.00161308 0.00164519 0.980 0.327251
## op_count:arg2 0.00639264 0.00008464 75.528 < 0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 122.3 on 588 degrees of freedom
## Multiple R-squared: 0.9873, Adjusted R-squared: 0.9872
## F-statistic: 9155 on 5 and 588 DF, p-value: < 0.00000000000000022
##
## [1] "COINBASE" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -147.949 -56.030 -9.611 45.916 235.943
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4183.9493 4.7623 878.55 <0.0000000000000002 ***
## op_count 10.2072 0.2488 41.02 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 73.21 on 576 degrees of freedom
## Multiple R-squared: 0.745, Adjusted R-squared: 0.7446
## F-statistic: 1683 on 1 and 576 DF, p-value: < 0.00000000000000022
##
## [1] "TIMESTAMP" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -133.727 -48.861 -9.727 39.139 206.139
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4148.5922 4.4536 931.52 <0.0000000000000002 ***
## op_count 7.8756 0.2288 34.43 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 68.03 on 581 degrees of freedom
## Multiple R-squared: 0.671, Adjusted R-squared: 0.6705
## F-statistic: 1185 on 1 and 581 DF, p-value: < 0.00000000000000022
##
## [1] "NUMBER" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -160.812 -62.812 -6.424 52.188 244.188
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4185.8120 5.3393 783.96 <0.0000000000000002 ***
## op_count 7.1741 0.2773 25.87 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 82.24 on 586 degrees of freedom
## Multiple R-squared: 0.5332, Adjusted R-squared: 0.5324
## F-statistic: 669.4 on 1 and 586 DF, p-value: < 0.00000000000000022
##
## [1] "DIFFICULTY" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -155.97 -61.97 -9.12 52.48 250.74
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4181.5562 5.1903 805.7 <0.0000000000000002 ***
## op_count 6.1806 0.2687 23.0 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 79.59 on 584 degrees of freedom
## Multiple R-squared: 0.4754, Adjusted R-squared: 0.4745
## F-statistic: 529.2 on 1 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "GASLIMIT" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -141.27 -56.26 -14.29 45.73 235.72
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4167.2845 4.9722 838.12 <0.0000000000000002 ***
## op_count 8.4659 0.2566 32.99 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 75.92 on 583 degrees of freedom
## Multiple R-squared: 0.6512, Adjusted R-squared: 0.6506
## F-statistic: 1088 on 1 and 583 DF, p-value: < 0.00000000000000022
##
## [1] "CHAINID" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -154.235 -66.235 -9.773 58.302 259.227
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4183.7728 5.4734 764.39 <0.0000000000000002 ***
## op_count 7.1642 0.2827 25.34 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 84.06 on 591 degrees of freedom
## Multiple R-squared: 0.5208, Adjusted R-squared: 0.52
## F-statistic: 642.3 on 1 and 591 DF, p-value: < 0.00000000000000022
##
## [1] "SELFBALANCE" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -142.53 -64.83 -15.53 58.37 253.37
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4160.4326 5.5125 754.7 <0.0000000000000002 ***
## op_count 29.0733 0.2863 101.6 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 84.91 on 586 degrees of freedom
## Multiple R-squared: 0.9462, Adjusted R-squared: 0.9461
## F-statistic: 1.031e+04 on 1 and 586 DF, p-value: < 0.00000000000000022
##
## [1] "POP" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -219.42 -114.31 -42.04 78.70 501.75
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14974.5304 14.4676 1035.040 <0.0000000000000002 ***
## op_count 5.1480 0.4936 10.430 <0.0000000000000002 ***
## arg0 0.7954 0.6422 1.239 0.216
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 144.3 on 571 degrees of freedom
## Multiple R-squared: 0.1613, Adjusted R-squared: 0.1584
## F-statistic: 54.92 on 2 and 571 DF, p-value: < 0.00000000000000022
##
## [1] "MLOAD" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -140.77 -49.46 -12.77 43.46 216.54
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 9272.0884874201 6.8869616877 1346.325 <0.0000000000000002 ***
## op_count 12.2460079519 0.2252425110 54.368 <0.0000000000000002 ***
## arg0 -0.0000009419 0.0005818367 -0.002 0.999
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 66.98 on 587 degrees of freedom
## Multiple R-squared: 0.8343, Adjusted R-squared: 0.8338
## F-statistic: 1478 on 2 and 587 DF, p-value: < 0.00000000000000022
##
## [1] "MSTORE" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -178.796 -48.289 -4.011 39.810 213.657
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8110.46111206 8.90946232 910.320 <0.0000000000000002 ***
## op_count 57.67483217 0.24202374 238.302 <0.0000000000000002 ***
## arg0 -0.00042528 0.00063034 -0.675 0.500
## arg1 0.00007288 0.00061766 0.118 0.906
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 72.24 on 584 degrees of freedom
## Multiple R-squared: 0.9898, Adjusted R-squared: 0.9898
## F-statistic: 1.893e+04 on 3 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "MSTORE8" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -131.943 -37.934 -1.883 32.643 156.550
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8088.7725817 6.1777083 1309.348 <0.0000000000000002 ***
## op_count 12.5246024 0.1750448 71.551 <0.0000000000000002 ***
## arg0 -0.0001151 0.0004666 -0.247 0.805
## arg1 0.0007507 0.0004680 1.604 0.109
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 51.91 on 584 degrees of freedom
## Multiple R-squared: 0.8976, Adjusted R-squared: 0.8971
## F-statistic: 1707 on 3 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "JUMP" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -187.20 -62.87 -4.87 50.96 270.80
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4442.8699 5.7778 768.95 <0.0000000000000002 ***
## op_count 29.6778 0.2976 99.72 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 88.04 on 583 degrees of freedom
## Multiple R-squared: 0.9446, Adjusted R-squared: 0.9445
## F-statistic: 9945 on 1 and 583 DF, p-value: < 0.00000000000000022
##
## [1] "JUMPI" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -313.1 -171.4 -8.0 102.1 600.0
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16347.5010 18.4722 884.981 <0.0000000000000002 ***
## op_count 53.8664 0.6575 81.932 <0.0000000000000002 ***
## arg0 -0.1522 0.8526 -0.179 0.858
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 193.7 on 576 degrees of freedom
## Multiple R-squared: 0.921, Adjusted R-squared: 0.9207
## F-statistic: 3357 on 2 and 576 DF, p-value: < 0.00000000000000022
##
## [1] "PC" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -144.66 -61.78 -13.66 55.14 231.18
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4174.660 5.344 781.13 <0.0000000000000002 ***
## op_count 5.344 0.276 19.36 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 81.12 on 580 degrees of freedom
## Multiple R-squared: 0.3926, Adjusted R-squared: 0.3916
## F-statistic: 375 on 1 and 580 DF, p-value: < 0.00000000000000022
##
## [1] "MSIZE" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -151.165 -62.394 -7.623 57.169 261.919
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4181.1646 5.2753 792.60 <0.0000000000000002 ***
## op_count 5.3944 0.2733 19.73 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 81.18 on 590 degrees of freedom
## Multiple R-squared: 0.3976, Adjusted R-squared: 0.3966
## F-statistic: 389.5 on 1 and 590 DF, p-value: < 0.00000000000000022
##
## [1] "GAS" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -150.25 -58.63 -11.25 51.12 218.75
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4167.8771 5.0946 818.09 <0.0000000000000002 ***
## op_count 5.8251 0.2629 22.16 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 78.48 on 590 degrees of freedom
## Multiple R-squared: 0.4542, Adjusted R-squared: 0.4532
## F-statistic: 490.9 on 1 and 590 DF, p-value: < 0.00000000000000022
##
## [1] "JUMPDEST" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -156.704 -56.704 -9.553 48.947 252.447
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3165.7043 4.7592 665.18 <0.0000000000000002 ***
## op_count 5.5232 0.2461 22.44 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 73.19 on 589 degrees of freedom
## Multiple R-squared: 0.4609, Adjusted R-squared: 0.46
## F-statistic: 503.5 on 1 and 589 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH1" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -143.106 -58.270 -7.215 50.562 231.785
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4166.1061 5.1266 812.65 <0.0000000000000002 ***
## op_count 5.7406 0.2655 21.62 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 78.35 on 584 degrees of freedom
## Multiple R-squared: 0.4446, Adjusted R-squared: 0.4436
## F-statistic: 467.5 on 1 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH2" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -148.736 -58.922 -9.329 52.264 223.671
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4168.922 5.226 797.69 <0.0000000000000002 ***
## op_count 8.094 0.269 30.09 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 80.08 on 585 degrees of freedom
## Multiple R-squared: 0.6075, Adjusted R-squared: 0.6069
## F-statistic: 905.5 on 1 and 585 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH3" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -211.734 -57.734 -6.734 61.834 266.834
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4148.1657 6.0539 685.20 <0.0000000000000002 ***
## op_count 15.3045 0.3133 48.85 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 92.8 on 583 degrees of freedom
## Multiple R-squared: 0.8037, Adjusted R-squared: 0.8034
## F-statistic: 2387 on 1 and 583 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH4" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -208.288 -58.309 -8.288 56.696 257.691
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4140.2660 6.0290 686.72 <0.0000000000000002 ***
## op_count 15.3348 0.3106 49.37 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 92.01 on 582 degrees of freedom
## Multiple R-squared: 0.8073, Adjusted R-squared: 0.8069
## F-statistic: 2438 on 1 and 582 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH5" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -201.130 -55.630 -3.356 58.370 249.097
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4132.9034 6.0292 685.49 <0.0000000000000002 ***
## op_count 15.0817 0.3108 48.52 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 91.83 on 581 degrees of freedom
## Multiple R-squared: 0.8021, Adjusted R-squared: 0.8017
## F-statistic: 2355 on 1 and 581 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH6" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -165.982 -64.416 0.018 50.801 213.801
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4195.9819 5.2156 804.5 <0.0000000000000002 ***
## op_count 14.7478 0.2686 54.9 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 79.48 on 583 degrees of freedom
## Multiple R-squared: 0.8379, Adjusted R-squared: 0.8376
## F-statistic: 3014 on 1 and 583 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH7" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -129.97 -70.16 -12.73 51.86 304.80
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4139.7316 5.7519 719.72 <0.0000000000000002 ***
## op_count 26.0823 0.2975 87.67 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 87.78 on 574 degrees of freedom
## Multiple R-squared: 0.9305, Adjusted R-squared: 0.9304
## F-statistic: 7687 on 1 and 574 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH8" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -137.37 -71.91 -13.07 51.84 265.21
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4153.9446 5.7566 721.60 <0.0000000000000002 ***
## op_count 24.4947 0.2991 81.89 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 88.37 on 580 degrees of freedom
## Multiple R-squared: 0.9204, Adjusted R-squared: 0.9203
## F-statistic: 6706 on 1 and 580 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH9" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -145.03 -72.70 -15.20 51.89 253.97
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4144.3663 5.7917 715.57 <0.0000000000000002 ***
## op_count 25.6888 0.2989 85.95 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 88.76 on 584 degrees of freedom
## Multiple R-squared: 0.9267, Adjusted R-squared: 0.9266
## F-statistic: 7388 on 1 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH10" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -141.92 -65.48 -15.30 53.70 262.46
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4150.2966 5.5268 750.94 <0.0000000000000002 ***
## op_count 24.2414 0.2844 85.22 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 84.9 on 588 degrees of freedom
## Multiple R-squared: 0.9251, Adjusted R-squared: 0.925
## F-statistic: 7263 on 1 and 588 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH11" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -140.61 -69.27 -16.27 46.89 305.05
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4145.2740 5.7415 721.99 <0.0000000000000002 ***
## op_count 24.4891 0.2946 83.12 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 87.61 on 584 degrees of freedom
## Multiple R-squared: 0.9221, Adjusted R-squared: 0.9219
## F-statistic: 6908 on 1 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH12" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -225.17 -93.67 0.33 70.02 347.89
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4101.235 7.706 532.24 <0.0000000000000002 ***
## op_count 32.396 0.397 81.59 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 118.7 on 590 degrees of freedom
## Multiple R-squared: 0.9186, Adjusted R-squared: 0.9185
## F-statistic: 6657 on 1 and 590 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH13" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -216.96 -104.71 0.66 90.73 322.92
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4108.8361 7.8284 524.86 <0.0000000000000002 ***
## op_count 31.8748 0.4044 78.82 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 120.4 on 584 degrees of freedom
## Multiple R-squared: 0.9141, Adjusted R-squared: 0.9139
## F-statistic: 6213 on 1 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH14" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -221.54 -100.54 10.73 80.73 268.73
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4104.2703 7.4574 550.36 <0.0000000000000002 ***
## op_count 31.9515 0.3853 82.93 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 113.1 on 571 degrees of freedom
## Multiple R-squared: 0.9233, Adjusted R-squared: 0.9232
## F-statistic: 6877 on 1 and 571 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH15" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -201.83 -88.54 -6.69 73.31 321.31
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4230.8343 7.1468 591.99 <0.0000000000000002 ***
## op_count 30.9236 0.3687 83.88 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 109.5 on 583 degrees of freedom
## Multiple R-squared: 0.9235, Adjusted R-squared: 0.9233
## F-statistic: 7035 on 1 and 583 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH16" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -168.32 -73.32 -16.21 62.01 299.68
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4175.2121 5.9905 697.0 <0.0000000000000002 ***
## op_count 40.8036 0.3087 132.2 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 92.25 on 590 degrees of freedom
## Multiple R-squared: 0.9673, Adjusted R-squared: 0.9673
## F-statistic: 1.747e+04 on 1 and 590 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH17" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -163.49 -64.68 -11.10 52.71 295.51
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4180.6021 5.6344 742.0 <0.0000000000000002 ***
## op_count 40.8295 0.2906 140.5 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 86.73 on 588 degrees of freedom
## Multiple R-squared: 0.9711, Adjusted R-squared: 0.971
## F-statistic: 1.975e+04 on 1 and 588 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH18" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -152.68 -62.68 -13.78 54.00 251.77
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4164.7790 5.5361 752.3 <0.0000000000000002 ***
## op_count 40.8300 0.2841 143.7 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 83.82 on 581 degrees of freedom
## Multiple R-squared: 0.9726, Adjusted R-squared: 0.9726
## F-statistic: 2.066e+04 on 1 and 581 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH19" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -148.98 -68.93 -11.98 55.02 259.09
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4175.9840 5.5642 750.5 <0.0000000000000002 ***
## op_count 39.3308 0.2881 136.5 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 85.88 on 589 degrees of freedom
## Multiple R-squared: 0.9694, Adjusted R-squared: 0.9693
## F-statistic: 1.864e+04 on 1 and 589 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH20" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -145.19 -62.26 -15.26 48.51 238.89
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4170.1142 5.1226 814.1 <0.0000000000000002 ***
## op_count 38.7382 0.2652 146.1 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 78.46 on 580 degrees of freedom
## Multiple R-squared: 0.9735, Adjusted R-squared: 0.9735
## F-statistic: 2.133e+04 on 1 and 580 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH21" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -225.778 -64.595 -4.145 67.538 280.589
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4134.1449 6.6592 620.8 <0.0000000000000002 ***
## op_count 48.0422 0.3449 139.3 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 101.5 on 581 degrees of freedom
## Multiple R-squared: 0.9709, Adjusted R-squared: 0.9709
## F-statistic: 1.94e+04 on 1 and 581 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH22" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -224.71 -69.27 -7.83 71.92 330.53
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4137.9488 7.0384 587.9 <0.0000000000000002 ***
## op_count 47.9842 0.3639 131.9 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 108.2 on 588 degrees of freedom
## Multiple R-squared: 0.9673, Adjusted R-squared: 0.9672
## F-statistic: 1.739e+04 on 1 and 588 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH23" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -228.386 -73.307 -1.544 80.114 293.456
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4116.2284 7.1215 578.0 <0.0000000000000002 ***
## op_count 47.7439 0.3681 129.7 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 108.9 on 581 degrees of freedom
## Multiple R-squared: 0.9666, Adjusted R-squared: 0.9666
## F-statistic: 1.683e+04 on 1 and 581 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH24" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -200.00 -88.62 -5.24 71.38 318.38
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4229.2447 7.2118 586.4 <0.0000000000000002 ***
## op_count 47.2920 0.3715 127.3 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 110.5 on 589 degrees of freedom
## Multiple R-squared: 0.9649, Adjusted R-squared: 0.9649
## F-statistic: 1.621e+04 on 1 and 589 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH25" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -177.65 -68.22 -11.22 59.56 280.35
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4180.2180 5.6309 742.4 <0.0000000000000002 ***
## op_count 56.7478 0.2922 194.2 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 86.89 on 587 degrees of freedom
## Multiple R-squared: 0.9847, Adjusted R-squared: 0.9846
## F-statistic: 3.771e+04 on 1 and 587 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH26" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -165.81 -72.74 -14.81 59.40 296.92
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4173.5343 6.1110 683.0 <0.0000000000000002 ***
## op_count 56.8183 0.3163 179.6 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 94.18 on 584 degrees of freedom
## Multiple R-squared: 0.9822, Adjusted R-squared: 0.9822
## F-statistic: 3.226e+04 on 1 and 584 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH27" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -155.55 -67.41 -12.41 55.56 313.45
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4157.4096 5.9257 701.6 <0.0000000000000002 ***
## op_count 57.1379 0.3044 187.7 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 90.05 on 581 degrees of freedom
## Multiple R-squared: 0.9838, Adjusted R-squared: 0.9838
## F-statistic: 3.524e+04 on 1 and 581 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH28" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -165.145 -67.135 -9.135 55.358 270.855
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4174.135 5.682 734.7 <0.0000000000000002 ***
## op_count 56.067 0.293 191.4 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 87.24 on 585 degrees of freedom
## Multiple R-squared: 0.9843, Adjusted R-squared: 0.9842
## F-statistic: 3.662e+04 on 1 and 585 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH29" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -167.12 -68.16 -14.16 55.80 299.88
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4170.2013 5.7952 719.6 <0.0000000000000002 ***
## op_count 55.9306 0.2986 187.3 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 88.92 on 583 degrees of freedom
## Multiple R-squared: 0.9836, Adjusted R-squared: 0.9836
## F-statistic: 3.507e+04 on 1 and 583 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH30" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -215.43 -69.95 -8.19 70.08 328.05
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4129.9168 6.6224 623.6 <0.0000000000000002 ***
## op_count 63.8343 0.3427 186.3 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 101.8 on 580 degrees of freedom
## Multiple R-squared: 0.9836, Adjusted R-squared: 0.9835
## F-statistic: 3.47e+04 on 1 and 580 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH31" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -209.72 -70.65 -6.72 69.13 336.43
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4122.8673 6.6626 618.8 <0.0000000000000002 ***
## op_count 64.4568 0.3441 187.3 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 102.2 on 586 degrees of freedom
## Multiple R-squared: 0.9836, Adjusted R-squared: 0.9835
## F-statistic: 3.51e+04 on 1 and 586 DF, p-value: < 0.00000000000000022
##
## [1] "PUSH32" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -232.879 -57.881 -6.879 61.122 246.122
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4145.8779 6.1701 671.9 <0.0000000000000002 ***
## op_count 61.8668 0.3203 193.2 <0.0000000000000002 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 94.87 on 586 degrees of freedom
## Multiple R-squared: 0.9845, Adjusted R-squared: 0.9845
## F-statistic: 3.732e+04 on 1 and 586 DF, p-value: < 0.00000000000000022
##
## [1] "DUP1" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -249.25 -127.90 -44.98 102.45 449.66
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16248.3285 15.8284 1026.528 <0.0000000000000002 ***
## op_count 6.0867 0.5313 11.457 <0.0000000000000002 ***
## arg0 1.2523 0.7061 1.774 0.0767 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 156.8 on 579 degrees of freedom
## Multiple R-squared: 0.1885, Adjusted R-squared: 0.1857
## F-statistic: 67.26 on 2 and 579 DF, p-value: < 0.00000000000000022
##
## [1] "DUP2" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -257.49 -124.26 -43.80 91.35 488.57
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16312.6156 15.7173 1037.875 < 0.0000000000000002 ***
## op_count 3.2453 0.5590 5.806 0.0000000107 ***
## arg0 -0.3561 0.7081 -0.503 0.615
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 163.4 on 567 degrees of freedom
## Multiple R-squared: 0.05658, Adjusted R-squared: 0.05325
## F-statistic: 17 on 2 and 567 DF, p-value: 0.00000006753
##
## [1] "DUP3" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -260.80 -135.79 -48.38 101.74 543.05
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16292.9718 17.1281 951.24 < 0.0000000000000002 ***
## op_count 4.3841 0.5799 7.56 0.000000000000156 ***
## arg0 0.1916 0.7996 0.24 0.811
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 172.6 on 584 degrees of freedom
## Multiple R-squared: 0.08923, Adjusted R-squared: 0.08611
## F-statistic: 28.61 on 2 and 584 DF, p-value: 0.000000000001404
##
## [1] "DUP4" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -247.49 -130.46 -32.33 92.61 459.38
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16291.0397 15.5223 1049.522 <0.0000000000000002 ***
## op_count 4.9162 0.5367 9.160 <0.0000000000000002 ***
## arg0 -0.4194 0.7007 -0.598 0.55
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 158.2 on 577 degrees of freedom
## Multiple R-squared: 0.1275, Adjusted R-squared: 0.1244
## F-statistic: 42.14 on 2 and 577 DF, p-value: < 0.00000000000000022
##
## [1] "DUP5" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -235.33 -132.25 -32.41 102.76 496.08
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16262.6203 15.4212 1054.564 <0.0000000000000002 ***
## op_count 5.9063 0.5339 11.063 <0.0000000000000002 ***
## arg0 0.1596 0.6794 0.235 0.814
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 157.3 on 572 degrees of freedom
## Multiple R-squared: 0.1763, Adjusted R-squared: 0.1734
## F-statistic: 61.2 on 2 and 572 DF, p-value: < 0.00000000000000022
##
## [1] "DUP6" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -203.35 -118.16 -51.62 93.26 470.52
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16236.3801 15.5103 1046.816 <0.0000000000000002 ***
## op_count 6.7246 0.5111 13.156 <0.0000000000000002 ***
## arg0 0.1614 0.6974 0.231 0.817
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 149.4 on 567 degrees of freedom
## Multiple R-squared: 0.2339, Adjusted R-squared: 0.2312
## F-statistic: 86.57 on 2 and 567 DF, p-value: < 0.00000000000000022
##
## [1] "DUP7" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -242.75 -134.25 -67.48 96.95 539.77
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16295.9008 17.1713 949.021 <0.0000000000000002 ***
## op_count 5.4964 0.5786 9.499 <0.0000000000000002 ***
## arg0 -0.7879 0.7954 -0.991 0.322
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 171.6 on 583 degrees of freedom
## Multiple R-squared: 0.135, Adjusted R-squared: 0.1321
## F-statistic: 45.51 on 2 and 583 DF, p-value: < 0.00000000000000022
##
## [1] "DUP8" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -289.24 -152.03 -22.22 111.91 520.86
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16316.8745 16.5350 986.808 <0.0000000000000002 ***
## op_count 15.0237 0.5841 25.721 <0.0000000000000002 ***
## arg0 0.1273 0.8079 0.158 0.875
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 172.8 on 580 degrees of freedom
## Multiple R-squared: 0.5329, Adjusted R-squared: 0.5313
## F-statistic: 330.8 on 2 and 580 DF, p-value: < 0.00000000000000022
##
## [1] "DUP9" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -224.71 -121.87 -56.77 88.23 532.31
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16271.6494 16.1544 1007.257 <0.0000000000000002 ***
## op_count 5.2956 0.5471 9.680 <0.0000000000000002 ***
## arg0 -0.3313 0.7614 -0.435 0.664
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 161.4 on 570 degrees of freedom
## Multiple R-squared: 0.1415, Adjusted R-squared: 0.1385
## F-statistic: 46.96 on 2 and 570 DF, p-value: < 0.00000000000000022
##
## [1] "DUP10" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -214.07 -123.37 -64.96 84.56 540.67
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16263.57536 16.61157 979.051 <0.0000000000000002 ***
## op_count 5.78936 0.56133 10.314 <0.0000000000000002 ***
## arg0 -0.08507 0.71765 -0.119 0.906
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 164.1 on 569 degrees of freedom
## Multiple R-squared: 0.1575, Adjusted R-squared: 0.1545
## F-statistic: 53.19 on 2 and 569 DF, p-value: < 0.00000000000000022
##
## [1] "DUP11" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -246.88 -131.29 -59.89 102.14 516.01
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16530.4922 16.9932 972.772 <0.0000000000000002 ***
## op_count 6.1565 0.5686 10.827 <0.0000000000000002 ***
## arg0 0.2717 0.7700 0.353 0.724
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 168.2 on 579 degrees of freedom
## Multiple R-squared: 0.1685, Adjusted R-squared: 0.1656
## F-statistic: 58.65 on 2 and 579 DF, p-value: < 0.00000000000000022
##
## [1] "DUP12" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -253.07 -136.26 -42.75 109.15 556.98
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16254.7355 16.2129 1002.58 <0.0000000000000002 ***
## op_count 5.8047 0.5695 10.19 <0.0000000000000002 ***
## arg0 1.5738 0.7288 2.16 0.0312 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 167.6 on 577 degrees of freedom
## Multiple R-squared: 0.1584, Adjusted R-squared: 0.1554
## F-statistic: 54.29 on 2 and 577 DF, p-value: < 0.00000000000000022
##
## [1] "DUP13" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -253.31 -128.28 -53.42 96.09 482.96
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16301.8196 16.6418 979.573 < 0.0000000000000002 ***
## op_count 4.4676 0.5525 8.086 0.00000000000000363 ***
## arg0 -1.1270 0.7427 -1.518 0.13
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 163 on 578 degrees of freedom
## Multiple R-squared: 0.1046, Adjusted R-squared: 0.1015
## F-statistic: 33.76 on 2 and 578 DF, p-value: 0.00000000000001357
##
## [1] "DUP14" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -200.20 -112.40 -45.00 85.07 400.12
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16278.4740 14.1736 1148.504 <0.0000000000000002 ***
## op_count 4.4041 0.4862 9.059 <0.0000000000000002 ***
## arg0 -0.8665 0.6587 -1.315 0.189
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 141.8 on 560 degrees of freedom
## Multiple R-squared: 0.1301, Adjusted R-squared: 0.127
## F-statistic: 41.89 on 2 and 560 DF, p-value: < 0.00000000000000022
##
## [1] "DUP15" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -234.35 -132.10 -49.14 95.06 500.89
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16294.7753 17.4660 932.942 < 0.0000000000000002 ***
## op_count 4.4803 0.5593 8.011 0.00000000000000625 ***
## arg0 -0.3113 0.7955 -0.391 0.696
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 165.4 on 581 degrees of freedom
## Multiple R-squared: 0.09962, Adjusted R-squared: 0.09652
## F-statistic: 32.14 on 2 and 581 DF, p-value: 0.00000000000005761
##
## [1] "DUP16" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -271.75 -154.14 -35.16 107.75 624.96
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 16885.4804 18.3031 922.55 <0.0000000000000002 ***
## op_count 14.7546 0.6171 23.91 <0.0000000000000002 ***
## arg0 -1.1521 0.8231 -1.40 0.162
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 182.6 on 577 degrees of freedom
## Multiple R-squared: 0.4987, Adjusted R-squared: 0.497
## F-statistic: 287 on 2 and 577 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP1" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -209.03 -108.05 -51.42 83.56 442.86
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14995.8805 18.0812 829.361 <0.0000000000000002 ***
## op_count 5.8010 0.4921 11.787 <0.0000000000000002 ***
## arg0 -0.8011 0.6614 -1.211 0.226
## arg1 0.6152 0.6425 0.957 0.339
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 143.7 on 566 degrees of freedom
## Multiple R-squared: 0.2003, Adjusted R-squared: 0.196
## F-statistic: 47.25 on 3 and 566 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP2" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -202.94 -107.67 -44.98 90.54 409.31
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14992.6528 17.3561 863.827 <0.0000000000000002 ***
## op_count 5.6791 0.4682 12.129 <0.0000000000000002 ***
## arg0 -0.2036 0.6500 -0.313 0.754
## arg1 0.4421 0.6099 0.725 0.469
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 136.5 on 568 degrees of freedom
## Multiple R-squared: 0.2065, Adjusted R-squared: 0.2023
## F-statistic: 49.28 on 3 and 568 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP3" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -218.43 -118.78 -34.94 84.60 458.62
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14989.8707 17.9332 835.871 <0.0000000000000002 ***
## op_count 5.4132 0.4960 10.914 <0.0000000000000002 ***
## arg0 0.3865 0.6575 0.588 0.557
## arg1 0.7537 0.6345 1.188 0.235
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 146 on 574 degrees of freedom
## Multiple R-squared: 0.174, Adjusted R-squared: 0.1697
## F-statistic: 40.3 on 3 and 574 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP4" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -191.64 -102.09 -44.70 75.79 435.68
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14970.83128 16.92458 884.562 <0.0000000000000002 ***
## op_count 6.85964 0.46058 14.893 <0.0000000000000002 ***
## arg0 0.08559 0.63284 0.135 0.892
## arg1 -0.12192 0.61056 -0.200 0.842
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 134.1 on 561 degrees of freedom
## Multiple R-squared: 0.2834, Adjusted R-squared: 0.2795
## F-statistic: 73.94 on 3 and 561 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP5" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -203.39 -119.45 -54.37 96.67 473.24
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14984.18205 19.24940 778.423 <0.0000000000000002 ***
## op_count 5.71312 0.49889 11.452 <0.0000000000000002 ***
## arg0 -0.05365 0.66363 -0.081 0.936
## arg1 1.13184 0.70932 1.596 0.111
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 147.2 on 578 degrees of freedom
## Multiple R-squared: 0.1881, Adjusted R-squared: 0.1839
## F-statistic: 44.64 on 3 and 578 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP6" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -236.73 -123.11 -56.57 84.78 470.72
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15256.33015 20.49706 744.318 <0.0000000000000002 ***
## op_count 6.49583 0.53153 12.221 <0.0000000000000002 ***
## arg0 -0.04294 0.71885 -0.060 0.952
## arg1 0.98149 0.70886 1.385 0.167
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 157.4 on 577 degrees of freedom
## Multiple R-squared: 0.2076, Adjusted R-squared: 0.2034
## F-statistic: 50.37 on 3 and 577 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP7" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -200.42 -108.70 -49.52 85.81 415.07
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15249.5236 17.4253 875.136 <0.0000000000000002 ***
## op_count 6.9700 0.4644 15.008 <0.0000000000000002 ***
## arg0 -0.3748 0.6464 -0.580 0.562
## arg1 0.2041 0.6629 0.308 0.758
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 136.5 on 573 degrees of freedom
## Multiple R-squared: 0.2825, Adjusted R-squared: 0.2787
## F-statistic: 75.19 on 3 and 573 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP8" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -210.92 -125.03 -54.19 96.18 475.95
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15013.6894 19.1365 784.558 <0.0000000000000002 ***
## op_count 5.4044 0.5378 10.049 <0.0000000000000002 ***
## arg0 0.5678 0.7119 0.798 0.425
## arg1 -0.4090 0.7280 -0.562 0.574
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 158.7 on 576 degrees of freedom
## Multiple R-squared: 0.1504, Adjusted R-squared: 0.146
## F-statistic: 33.98 on 3 and 576 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP9" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -208.86 -109.95 -43.98 77.70 430.13
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14961.5378 18.3411 815.737 <0.0000000000000002 ***
## op_count 6.2049 0.4649 13.347 <0.0000000000000002 ***
## arg0 0.9615 0.6550 1.468 0.143
## arg1 0.3701 0.6271 0.590 0.555
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 137.2 on 574 degrees of freedom
## Multiple R-squared: 0.2391, Adjusted R-squared: 0.2351
## F-statistic: 60.12 on 3 and 574 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP10" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -204.11 -117.41 -53.90 84.65 497.78
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15549.91828 19.40572 801.306 <0.0000000000000002 ***
## op_count 4.92447 0.50419 9.767 <0.0000000000000002 ***
## arg0 0.71646 0.65344 1.096 0.273
## arg1 0.02569 0.71647 0.036 0.971
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 147.6 on 565 degrees of freedom
## Multiple R-squared: 0.146, Adjusted R-squared: 0.1415
## F-statistic: 32.2 on 3 and 565 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP11" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -212.89 -122.01 -58.65 90.41 535.54
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14996.4993 19.3487 775.067 <0.0000000000000002 ***
## op_count 4.9341 0.5338 9.244 <0.0000000000000002 ***
## arg0 1.0242 0.7297 1.404 0.161
## arg1 0.3789 0.7303 0.519 0.604
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 156.7 on 570 degrees of freedom
## Multiple R-squared: 0.1333, Adjusted R-squared: 0.1287
## F-statistic: 29.21 on 3 and 570 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP12" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -214.63 -110.80 -48.17 88.58 426.06
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15225.78039 16.76790 908.032 <0.0000000000000002 ***
## op_count 7.41690 0.48829 15.190 <0.0000000000000002 ***
## arg0 1.11360 0.63087 1.765 0.0781 .
## arg1 0.02576 0.64380 0.040 0.9681
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 141.5 on 559 degrees of freedom
## Multiple R-squared: 0.2964, Adjusted R-squared: 0.2926
## F-statistic: 78.5 on 3 and 559 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP13" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -212.82 -117.08 -38.08 91.26 422.26
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15278.33846 17.26562 884.900 <0.0000000000000002 ***
## op_count 5.24882 0.49206 10.667 <0.0000000000000002 ***
## arg0 0.08079 0.65844 0.123 0.902
## arg1 0.97306 0.64912 1.499 0.134
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 145.6 on 574 degrees of freedom
## Multiple R-squared: 0.1688, Adjusted R-squared: 0.1644
## F-statistic: 38.85 on 3 and 574 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP14" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -225.54 -112.06 -35.74 81.83 474.37
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15019.78954 17.27320 869.543 <0.0000000000000002 ***
## op_count 4.50499 0.48496 9.289 <0.0000000000000002 ***
## arg0 -0.01224 0.68189 -0.018 0.986
## arg1 0.14742 0.64851 0.227 0.820
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 142.7 on 572 degrees of freedom
## Multiple R-squared: 0.1311, Adjusted R-squared: 0.1266
## F-statistic: 28.78 on 3 and 572 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP15" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -212.27 -98.04 -45.80 80.83 448.52
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15775.8130 17.0925 922.968 <0.0000000000000002 ***
## op_count 7.5993 0.4478 16.969 <0.0000000000000002 ***
## arg0 -0.5215 0.5975 -0.873 0.383
## arg1 -0.5598 0.5974 -0.937 0.349
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 130.9 on 566 degrees of freedom
## Multiple R-squared: 0.339, Adjusted R-squared: 0.3355
## F-statistic: 96.75 on 3 and 566 DF, p-value: < 0.00000000000000022
##
## [1] "SWAP16" "erigon"
##
## Call:
## lm(formula = formula, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -209.03 -106.02 -54.79 87.69 427.91
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15495.9954 17.5808 881.418 <0.0000000000000002 ***
## op_count 6.9934 0.4755 14.707 <0.0000000000000002 ***
## arg0 0.8874 0.6091 1.457 0.146
## arg1 0.5587 0.6551 0.853 0.394
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 139.2 on 568 degrees of freedom
## Multiple R-squared: 0.2783, Adjusted R-squared: 0.2745
## F-statistic: 73.01 on 3 and 568 DF, p-value: < 0.00000000000000022estimates## opcode env has_significant has_impacting estimate_marginal_ns
## 1 ADD erigon FALSE FALSE 6.68005832650455
## 2 MUL erigon FALSE FALSE 7.81664447982909
## 3 SUB erigon FALSE FALSE 5.23973232027987
## 4 DIV erigon TRUE TRUE 8.5062198966197
## 5 SDIV erigon TRUE TRUE 10.1454908494465
## 6 MOD erigon TRUE TRUE 11.2224557363261
## 7 SMOD erigon TRUE TRUE 12.6919876893462
## 8 ADDMOD erigon TRUE TRUE 9.65894788350503
## 9 MULMOD erigon TRUE TRUE 27.2232476150595
## 10 EXP erigon TRUE TRUE -2.94475877725044
## 11 SIGNEXTEND erigon FALSE FALSE 6.86706749046986
## 12 LT erigon FALSE FALSE 6.71755688247361
## 13 GT erigon FALSE FALSE 5.51796375069022
## 14 SLT erigon FALSE FALSE 8.54057663834166
## 15 SGT erigon FALSE FALSE 8.4644884899419
## 16 EQ erigon FALSE FALSE 6.12423065552128
## 17 ISZERO erigon FALSE FALSE 3.91729014443924
## 18 AND erigon FALSE FALSE 5.19302920030162
## 19 OR erigon FALSE FALSE 6.32587842705802
## 20 XOR erigon FALSE FALSE 3.65425081360411
## 21 NOT erigon FALSE FALSE 4.14440153128572
## 22 BYTE erigon FALSE FALSE 6.73232766406074
## 23 SHL erigon FALSE FALSE 4.36688866693836
## 24 SHR erigon FALSE FALSE 5.83209240699214
## 25 SAR erigon FALSE FALSE 5.58087178987759
## 26 ADDRESS erigon FALSE FALSE 19.4060518678402
## 27 ORIGIN erigon FALSE FALSE 10.44021817092
## 28 CALLER erigon FALSE FALSE 9.52634721168999
## 29 CALLVALUE erigon FALSE FALSE 5.04248847659922
## 30 CALLDATALOAD erigon FALSE FALSE 6.81629797256189
## 31 CALLDATASIZE erigon FALSE FALSE 5.72336769759445
## 32 CALLDATACOPY erigon TRUE TRUE 26.1077005430581
## 33 CODESIZE erigon FALSE FALSE 5.83702160962405
## 34 CODECOPY erigon TRUE TRUE 37.077840976205
## 35 GASPRICE erigon FALSE FALSE 6.17756587523899
## 36 RETURNDATASIZE erigon FALSE FALSE 5.08570708888086
## 37 RETURNDATACOPY erigon TRUE TRUE 21.3297027437363
## 38 COINBASE erigon FALSE FALSE 10.2072089408852
## 39 TIMESTAMP erigon FALSE FALSE 7.87562684591105
## 40 NUMBER erigon FALSE FALSE 7.17410363822754
## 41 DIFFICULTY erigon FALSE FALSE 6.18060349354144
## 42 GASLIMIT erigon FALSE FALSE 8.4659342719703
## 43 CHAINID erigon FALSE FALSE 7.16416703855
## 44 SELFBALANCE erigon FALSE FALSE 29.0732578456577
## 45 POP erigon FALSE FALSE 5.14801770089041
## 46 MLOAD erigon FALSE FALSE 12.2460079519442
## 47 MSTORE erigon FALSE FALSE 57.6748321674116
## 48 MSTORE8 erigon FALSE FALSE 12.5246023896036
## 49 JUMP erigon FALSE FALSE 29.6777874457275
## 50 JUMPI erigon FALSE FALSE 53.8664054750097
## 51 PC erigon FALSE FALSE 5.34415886595907
## 52 MSIZE erigon FALSE FALSE 5.39441523743856
## 53 GAS erigon FALSE FALSE 5.82508417508417
## 54 JUMPDEST erigon FALSE FALSE 5.52324903198401
## 55 PUSH1 erigon FALSE FALSE 5.74060554749593
## 56 PUSH2 erigon FALSE FALSE 8.09379725635684
## 57 PUSH3 erigon FALSE FALSE 15.3045242958456
## 58 PUSH4 erigon FALSE FALSE 15.3347734710245
## 59 PUSH5 erigon FALSE FALSE 15.0817424108458
## 60 PUSH6 erigon FALSE FALSE 14.7477983441438
## 61 PUSH7 erigon FALSE FALSE 26.0823254958432
## 62 PUSH8 erigon FALSE FALSE 24.4947063513156
## 63 PUSH9 erigon FALSE FALSE 25.688775510204
## 64 PUSH10 erigon FALSE FALSE 24.2414416728014
## 65 PUSH11 erigon FALSE FALSE 24.489050243262
## 66 PUSH12 erigon FALSE FALSE 32.3959405391526
## 67 PUSH13 erigon FALSE FALSE 31.8747741972739
## 68 PUSH14 erigon FALSE FALSE 31.9515305889964
## 69 PUSH15 erigon FALSE FALSE 30.9236394557824
## 70 PUSH16 erigon FALSE FALSE 40.8036495718855
## 71 PUSH17 erigon FALSE FALSE 40.829461279461
## 72 PUSH18 erigon FALSE FALSE 40.8300418491655
## 73 PUSH19 erigon FALSE FALSE 39.3307741736494
## 74 PUSH20 erigon FALSE FALSE 38.7382284474952
## 75 PUSH21 erigon FALSE FALSE 48.0422126582726
## 76 PUSH22 erigon FALSE FALSE 47.9841749723625
## 77 PUSH23 erigon FALSE FALSE 47.7438536770343
## 78 PUSH24 erigon FALSE FALSE 47.2919639704806
## 79 PUSH25 erigon FALSE FALSE 56.7477818294935
## 80 PUSH26 erigon FALSE FALSE 56.818314072688
## 81 PUSH27 erigon FALSE FALSE 57.1378937682094
## 82 PUSH28 erigon FALSE FALSE 56.0670050761421
## 83 PUSH29 erigon FALSE FALSE 55.9306260575296
## 84 PUSH30 erigon FALSE FALSE 63.8343070556883
## 85 PUSH31 erigon FALSE FALSE 64.456802721088
## 86 PUSH32 erigon FALSE FALSE 61.8667550500641
## 87 DUP1 erigon FALSE FALSE 6.08673055353322
## 88 DUP2 erigon FALSE FALSE 3.24533136105295
## 89 DUP3 erigon FALSE FALSE 4.38412056946785
## 90 DUP4 erigon FALSE FALSE 4.916182022455
## 91 DUP5 erigon FALSE FALSE 5.90628138754152
## 92 DUP6 erigon FALSE FALSE 6.7245912305929
## 93 DUP7 erigon FALSE FALSE 5.4964196420518
## 94 DUP8 erigon FALSE FALSE 15.0236751232396
## 95 DUP9 erigon FALSE FALSE 5.29557474236041
## 96 DUP10 erigon FALSE FALSE 5.78936497490813
## 97 DUP11 erigon FALSE FALSE 6.15646585561814
## 98 DUP12 erigon FALSE FALSE 5.80465708201686
## 99 DUP13 erigon FALSE FALSE 4.46755184964527
## 100 DUP14 erigon FALSE FALSE 4.404093299742
## 101 DUP15 erigon FALSE FALSE 4.48033975940476
## 102 DUP16 erigon FALSE FALSE 14.7545927303432
## 103 SWAP1 erigon FALSE FALSE 5.80098742534723
## 104 SWAP2 erigon FALSE FALSE 5.67913795717462
## 105 SWAP3 erigon FALSE FALSE 5.4131557752245
## 106 SWAP4 erigon FALSE FALSE 6.85964224128208
## 107 SWAP5 erigon FALSE FALSE 5.71312088534721
## 108 SWAP6 erigon FALSE FALSE 6.49582714660794
## 109 SWAP7 erigon FALSE FALSE 6.97003827385409
## 110 SWAP8 erigon FALSE FALSE 5.40436891358659
## 111 SWAP9 erigon FALSE FALSE 6.20491900506547
## 112 SWAP10 erigon FALSE FALSE 4.92446584770607
## 113 SWAP11 erigon FALSE FALSE 4.93412077499299
## 114 SWAP12 erigon FALSE FALSE 7.41689524309915
## 115 SWAP13 erigon FALSE FALSE 5.24882298106487
## 116 SWAP14 erigon FALSE FALSE 4.50498934333396
## 117 SWAP15 erigon FALSE FALSE 7.5993203441866
## 118 SWAP16 erigon FALSE FALSE 6.99336128499169
## arg0_ns arg1_ns arg2_ns expensive_ns
## 1 <NA> <NA> <NA> <NA>
## 2 <NA> <NA> <NA> <NA>
## 3 <NA> <NA> <NA> <NA>
## 4 <NA> <NA> <NA> 17.2493755983365
## 5 <NA> <NA> <NA> 18.4079094614616
## 6 <NA> <NA> <NA> 15.2856202006643
## 7 <NA> <NA> <NA> 14.1011121191467
## 8 <NA> <NA> <NA> 22.6996028571847
## 9 <NA> <NA> <NA> 22.0172643836436
## 10 <NA> 84.6379295646096 <NA> <NA>
## 11 <NA> <NA> <NA> <NA>
## 12 <NA> <NA> <NA> <NA>
## 13 <NA> <NA> <NA> <NA>
## 14 <NA> <NA> <NA> <NA>
## 15 <NA> <NA> <NA> <NA>
## 16 <NA> <NA> <NA> <NA>
## 17 <NA> <NA> <NA> <NA>
## 18 <NA> <NA> <NA> <NA>
## 19 <NA> <NA> <NA> <NA>
## 20 <NA> <NA> <NA> <NA>
## 21 <NA> <NA> <NA> <NA>
## 22 <NA> <NA> <NA> <NA>
## 23 <NA> <NA> <NA> <NA>
## 24 <NA> <NA> <NA> <NA>
## 25 <NA> <NA> <NA> <NA>
## 26 <NA> <NA> <NA> <NA>
## 27 <NA> <NA> <NA> <NA>
## 28 <NA> <NA> <NA> <NA>
## 29 <NA> <NA> <NA> <NA>
## 30 <NA> <NA> <NA> <NA>
## 31 <NA> <NA> <NA> <NA>
## 32 <NA> <NA> 0.00653902267724568 <NA>
## 33 <NA> <NA> <NA> <NA>
## 34 <NA> <NA> 0.0781750910415538 <NA>
## 35 <NA> <NA> <NA> <NA>
## 36 <NA> <NA> <NA> <NA>
## 37 <NA> <NA> 0.00639263790020834 <NA>
## 38 <NA> <NA> <NA> <NA>
## 39 <NA> <NA> <NA> <NA>
## 40 <NA> <NA> <NA> <NA>
## 41 <NA> <NA> <NA> <NA>
## 42 <NA> <NA> <NA> <NA>
## 43 <NA> <NA> <NA> <NA>
## 44 <NA> <NA> <NA> <NA>
## 45 <NA> <NA> <NA> <NA>
## 46 <NA> <NA> <NA> <NA>
## 47 <NA> <NA> <NA> <NA>
## 48 <NA> <NA> <NA> <NA>
## 49 <NA> <NA> <NA> <NA>
## 50 <NA> <NA> <NA> <NA>
## 51 <NA> <NA> <NA> <NA>
## 52 <NA> <NA> <NA> <NA>
## 53 <NA> <NA> <NA> <NA>
## 54 <NA> <NA> <NA> <NA>
## 55 <NA> <NA> <NA> <NA>
## 56 <NA> <NA> <NA> <NA>
## 57 <NA> <NA> <NA> <NA>
## 58 <NA> <NA> <NA> <NA>
## 59 <NA> <NA> <NA> <NA>
## 60 <NA> <NA> <NA> <NA>
## 61 <NA> <NA> <NA> <NA>
## 62 <NA> <NA> <NA> <NA>
## 63 <NA> <NA> <NA> <NA>
## 64 <NA> <NA> <NA> <NA>
## 65 <NA> <NA> <NA> <NA>
## 66 <NA> <NA> <NA> <NA>
## 67 <NA> <NA> <NA> <NA>
## 68 <NA> <NA> <NA> <NA>
## 69 <NA> <NA> <NA> <NA>
## 70 <NA> <NA> <NA> <NA>
## 71 <NA> <NA> <NA> <NA>
## 72 <NA> <NA> <NA> <NA>
## 73 <NA> <NA> <NA> <NA>
## 74 <NA> <NA> <NA> <NA>
## 75 <NA> <NA> <NA> <NA>
## 76 <NA> <NA> <NA> <NA>
## 77 <NA> <NA> <NA> <NA>
## 78 <NA> <NA> <NA> <NA>
## 79 <NA> <NA> <NA> <NA>
## 80 <NA> <NA> <NA> <NA>
## 81 <NA> <NA> <NA> <NA>
## 82 <NA> <NA> <NA> <NA>
## 83 <NA> <NA> <NA> <NA>
## 84 <NA> <NA> <NA> <NA>
## 85 <NA> <NA> <NA> <NA>
## 86 <NA> <NA> <NA> <NA>
## 87 <NA> <NA> <NA> <NA>
## 88 <NA> <NA> <NA> <NA>
## 89 <NA> <NA> <NA> <NA>
## 90 <NA> <NA> <NA> <NA>
## 91 <NA> <NA> <NA> <NA>
## 92 <NA> <NA> <NA> <NA>
## 93 <NA> <NA> <NA> <NA>
## 94 <NA> <NA> <NA> <NA>
## 95 <NA> <NA> <NA> <NA>
## 96 <NA> <NA> <NA> <NA>
## 97 <NA> <NA> <NA> <NA>
## 98 <NA> <NA> <NA> <NA>
## 99 <NA> <NA> <NA> <NA>
## 100 <NA> <NA> <NA> <NA>
## 101 <NA> <NA> <NA> <NA>
## 102 <NA> <NA> <NA> <NA>
## 103 <NA> <NA> <NA> <NA>
## 104 <NA> <NA> <NA> <NA>
## 105 <NA> <NA> <NA> <NA>
## 106 <NA> <NA> <NA> <NA>
## 107 <NA> <NA> <NA> <NA>
## 108 <NA> <NA> <NA> <NA>
## 109 <NA> <NA> <NA> <NA>
## 110 <NA> <NA> <NA> <NA>
## 111 <NA> <NA> <NA> <NA>
## 112 <NA> <NA> <NA> <NA>
## 113 <NA> <NA> <NA> <NA>
## 114 <NA> <NA> <NA> <NA>
## 115 <NA> <NA> <NA> <NA>
## 116 <NA> <NA> <NA> <NA>
## 117 <NA> <NA> <NA> <NA>
## 118 <NA> <NA> <NA> <NA>
## arg0_ns_stderr arg1_ns_stderr arg2_ns_stderr expensive_ns_stderr
## 1 <NA> <NA> <NA> <NA>
## 2 <NA> <NA> <NA> <NA>
## 3 <NA> <NA> <NA> <NA>
## 4 <NA> <NA> <NA> 1.20864801081364
## 5 <NA> <NA> <NA> 1.13055577800986
## 6 <NA> <NA> <NA> 1.21838579535245
## 7 <NA> <NA> <NA> 1.19270276869283
## 8 <NA> <NA> <NA> 1.2427704147369
## 9 <NA> <NA> <NA> 1.58806616033603
## 10 <NA> 0.269881497779208 <NA> <NA>
## 11 <NA> <NA> <NA> <NA>
## 12 <NA> <NA> <NA> <NA>
## 13 <NA> <NA> <NA> <NA>
## 14 <NA> <NA> <NA> <NA>
## 15 <NA> <NA> <NA> <NA>
## 16 <NA> <NA> <NA> <NA>
## 17 <NA> <NA> <NA> <NA>
## 18 <NA> <NA> <NA> <NA>
## 19 <NA> <NA> <NA> <NA>
## 20 <NA> <NA> <NA> <NA>
## 21 <NA> <NA> <NA> <NA>
## 22 <NA> <NA> <NA> <NA>
## 23 <NA> <NA> <NA> <NA>
## 24 <NA> <NA> <NA> <NA>
## 25 <NA> <NA> <NA> <NA>
## 26 <NA> <NA> <NA> <NA>
## 27 <NA> <NA> <NA> <NA>
## 28 <NA> <NA> <NA> <NA>
## 29 <NA> <NA> <NA> <NA>
## 30 <NA> <NA> <NA> <NA>
## 31 <NA> <NA> <NA> <NA>
## 32 <NA> <NA> 0.0000930873382232063 <NA>
## 33 <NA> <NA> <NA> <NA>
## 34 <NA> <NA> 0.00117821458185962 <NA>
## 35 <NA> <NA> <NA> <NA>
## 36 <NA> <NA> <NA> <NA>
## 37 <NA> <NA> 0.0000846397533078088 <NA>
## 38 <NA> <NA> <NA> <NA>
## 39 <NA> <NA> <NA> <NA>
## 40 <NA> <NA> <NA> <NA>
## 41 <NA> <NA> <NA> <NA>
## 42 <NA> <NA> <NA> <NA>
## 43 <NA> <NA> <NA> <NA>
## 44 <NA> <NA> <NA> <NA>
## 45 <NA> <NA> <NA> <NA>
## 46 <NA> <NA> <NA> <NA>
## 47 <NA> <NA> <NA> <NA>
## 48 <NA> <NA> <NA> <NA>
## 49 <NA> <NA> <NA> <NA>
## 50 <NA> <NA> <NA> <NA>
## 51 <NA> <NA> <NA> <NA>
## 52 <NA> <NA> <NA> <NA>
## 53 <NA> <NA> <NA> <NA>
## 54 <NA> <NA> <NA> <NA>
## 55 <NA> <NA> <NA> <NA>
## 56 <NA> <NA> <NA> <NA>
## 57 <NA> <NA> <NA> <NA>
## 58 <NA> <NA> <NA> <NA>
## 59 <NA> <NA> <NA> <NA>
## 60 <NA> <NA> <NA> <NA>
## 61 <NA> <NA> <NA> <NA>
## 62 <NA> <NA> <NA> <NA>
## 63 <NA> <NA> <NA> <NA>
## 64 <NA> <NA> <NA> <NA>
## 65 <NA> <NA> <NA> <NA>
## 66 <NA> <NA> <NA> <NA>
## 67 <NA> <NA> <NA> <NA>
## 68 <NA> <NA> <NA> <NA>
## 69 <NA> <NA> <NA> <NA>
## 70 <NA> <NA> <NA> <NA>
## 71 <NA> <NA> <NA> <NA>
## 72 <NA> <NA> <NA> <NA>
## 73 <NA> <NA> <NA> <NA>
## 74 <NA> <NA> <NA> <NA>
## 75 <NA> <NA> <NA> <NA>
## 76 <NA> <NA> <NA> <NA>
## 77 <NA> <NA> <NA> <NA>
## 78 <NA> <NA> <NA> <NA>
## 79 <NA> <NA> <NA> <NA>
## 80 <NA> <NA> <NA> <NA>
## 81 <NA> <NA> <NA> <NA>
## 82 <NA> <NA> <NA> <NA>
## 83 <NA> <NA> <NA> <NA>
## 84 <NA> <NA> <NA> <NA>
## 85 <NA> <NA> <NA> <NA>
## 86 <NA> <NA> <NA> <NA>
## 87 <NA> <NA> <NA> <NA>
## 88 <NA> <NA> <NA> <NA>
## 89 <NA> <NA> <NA> <NA>
## 90 <NA> <NA> <NA> <NA>
## 91 <NA> <NA> <NA> <NA>
## 92 <NA> <NA> <NA> <NA>
## 93 <NA> <NA> <NA> <NA>
## 94 <NA> <NA> <NA> <NA>
## 95 <NA> <NA> <NA> <NA>
## 96 <NA> <NA> <NA> <NA>
## 97 <NA> <NA> <NA> <NA>
## 98 <NA> <NA> <NA> <NA>
## 99 <NA> <NA> <NA> <NA>
## 100 <NA> <NA> <NA> <NA>
## 101 <NA> <NA> <NA> <NA>
## 102 <NA> <NA> <NA> <NA>
## 103 <NA> <NA> <NA> <NA>
## 104 <NA> <NA> <NA> <NA>
## 105 <NA> <NA> <NA> <NA>
## 106 <NA> <NA> <NA> <NA>
## 107 <NA> <NA> <NA> <NA>
## 108 <NA> <NA> <NA> <NA>
## 109 <NA> <NA> <NA> <NA>
## 110 <NA> <NA> <NA> <NA>
## 111 <NA> <NA> <NA> <NA>
## 112 <NA> <NA> <NA> <NA>
## 113 <NA> <NA> <NA> <NA>
## 114 <NA> <NA> <NA> <NA>
## 115 <NA> <NA> <NA> <NA>
## 116 <NA> <NA> <NA> <NA>
## 117 <NA> <NA> <NA> <NA>
## 118 <NA> <NA> <NA> <NA>write.csv(estimates, paste0("../../local/", env, "_argument_estimated_cost.csv"), quote=FALSE, row.names=FALSE)